# Best ETL Tools *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Databricks is the top-ranked ETL tool in 2026, rated 4.6 out of 5 on G2 based on 1,300+ verified reviews. Celigo stands out as the highest-rated option at 4.7 stars, particularly favored by NetSuite-centric organizations seeking seamless app integration and ease of use. 1. Databricks — 4.6/5 (1,300+ reviews): Unified lakehouse pipelines with governance and ML workflows 2. Celigo — 4.6/5 (1,000+ reviews): NetSuite-centered app integration and sync 3. Google Cloud BigQuery — 4.5/5 (1,200+ reviews): Serverless analytics on large cloud datasets 4. Alteryx — 4.6/5 (800+ reviews): Drag-and-drop data prep and reporting automation 5. IBM watsonx.data — 4.4/5 (100+ reviews): Lakehouse querying across object storage *Updated June 2026. Based on 2026 G2 verified review data across 1,780 products.* ETL (extract, transform, and load) tools transfer data between databases and external systems, supporting data replication, warehousing, analytics, data cleansing, and structuring, and increasingly support ELT workflows where transformation occurs within the target system rather than before loading. ### Core Capabilities of ETL Tools To qualify for inclusion in the ETL category, a product must: - Facilitate extract, transform, and load processes - Transform data for quality or visualization - Audit or record integration data - Archive data for backup, future reference, or analysis ### Common Use Cases for ETL Tools Data engineering and analytics teams use ETL tools to move and prepare data for reporting, analysis, and business intelligence. Common use cases include: - Replicating data from source systems into [data warehouses](https://www.g2.com/categories/data-warehouse) for centralized analytics - Cleansing and transforming raw data into structured, queryable formats - Building visual data workflows to automate recurring data transfer and integration processes ### How ETL Tools Differ from Other Tools ETL tools pre-process and transform data before loading it into the target system, distinguishing them from ELT approaches where the target system handles transformation after loading. While [data integration tools](https://www.g2.com/categories/data-integration-tools) cover a broader range of connectivity scenarios, ETL tools focus specifically on structured data movement pipelines with built-in transformation, auditing, and archiving capabilities. ### Insights from G2 on ETL Tools Based on category trends on G2, visual workflow builders and pre-built connectors stand out as standout features. These platforms deliver reductions in manual data preparation time and improved data quality as core benefits of ETL adoption. ## Top ETL Tools at a Glance | # | Product | Rating | Best For | What Users Say | |---|---------|--------|----------|----------------| | 1 | [Databricks](https://www.g2.com/products/databricks/reviews) | 4.6/5.0 (1,284 reviews) | Unified lakehouse pipelines with governance and ML workflows | "[Powerful Lakehouse for Big Data, Collaboration, and Efficient Pipelines](https://www.g2.com/survey_responses/databricks-review-12946286)" | | 2 | [Celigo](https://www.g2.com/products/celigo/reviews) | 4.6/5.0 (1,018 reviews) | NetSuite-centered app integration and sync | "[Go for it if you’re looking for a solid integration platform](https://www.g2.com/survey_responses/celigo-review-11876505)" | | 3 | [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) | 4.5/5.0 (1,147 reviews) | Serverless analytics on large cloud datasets | "[Easy-to-Use Cloud Tool with Shareable, Saved Queries](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)" | | 4 | [Alteryx](https://www.g2.com/products/alteryx/reviews) | 4.6/5.0 (822 reviews) | Drag-and-drop data prep and reporting automation | "[Intuitive Drag-and-Drop Analytics That Speeds Up Data Prep and Insights](https://www.g2.com/survey_responses/alteryx-review-12983224)" | | 5 | [IBM watsonx.data](https://www.g2.com/products/ibm-watsonx-data/reviews) | 4.4/5.0 (159 reviews) | Lakehouse querying across object storage | "[Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)" | | 6 | [FME Platform](https://www.g2.com/products/fme-platform/reviews) | 4.6/5.0 (124 reviews) | Geospatial and multi-format data transformation | "[FME Saves Time with Powerful GIS ETL and Automation](https://www.g2.com/survey_responses/fme-platform-review-12863747)" | | 7 | [Fivetran](https://www.g2.com/products/fivetran/reviews) | 4.3/5.0 (782 reviews) | Managed connector-based data ingestion | "[Trouble-Free Data Pipelines with Effortless Connections to Nearly Every Service](https://www.g2.com/survey_responses/fivetran-review-12999542)" | | 8 | [Domo](https://www.g2.com/products/domo/reviews) | 4.3/5.0 (994 reviews) | Self-service ETL feeding business dashboards | "[All-in-One Platform for Real-Time Analytics and Dashboards](https://www.g2.com/survey_responses/domo-review-12676104)" | | 9 | [Workato](https://www.g2.com/products/workato/reviews) | 4.7/5.0 (749 reviews) | Low-code workflow automation across SaaS apps | "[Workato helps us building complex integrations at lightning speed.](https://www.g2.com/survey_responses/workato-review-10305521)" | | 10 | [Skyvia](https://www.g2.com/products/skyvia/reviews) | 4.8/5.0 (322 reviews) | No-code CRM sync, backup, and scheduled ETL | "[Reliable Data Integration Without the Headache](https://www.g2.com/survey_responses/skyvia-review-12998949)" | --- ## What Are the Most Common Questions About ETL Tools? *AI-generated · Last updated: May 26, 2026* ### How to evaluate ETL tools based on performance and transformation logic? Based on G2 reviews, buyers evaluating ETL tools for performance and transformation logic should focus on how well platforms handle large data volumes, connect multiple sources, and support dependable transformations without excessive manual work. According to verified users, strong options are often described as fast, scalable, and capable of simplifying complex workflows while supporting SQL, APIs, batch jobs, or real-time processing. G2 reviewers mention that practical evaluation also comes down to how easy pipelines are to debug, how clearly data flows can be monitored, and whether transformations can be reused or automated. Reviews also consistently call out tradeoffs such as steep learning curves, slow troubleshooting, or heavy resource use, so teams should weigh speed and flexibility against maintainability. ### What best ETL platforms with version control and team collaboration features? Based on G2 reviews, Databricks stands out strongly for ETL teams that want version-aware development and collaboration in one environment. According to verified users, Databricks is frequently praised for shared notebooks, Git-based repo sync, CI/CD support, and a workspace that helps engineers, analysts, and data teams work together on pipelines, transformations, and analytics. G2 reviewers mention that these collaboration features help reduce coordination overhead and make onboarding easier, especially when multiple users are working across notebooks and workflows. At the same time, reviewers also note tradeoffs such as workspace sprawl, UI complexity at scale, and the need for discipline around administration and cost control. Overall, recent reviews point to Databricks as the clearest single-product leader here. **Here are some of the top-rated products on G2:** - [Databricks](https://www.g2.com/products/databricks/reviews) – used for shared notebooks, Git-based repo sync, collaborative ETL workflows, and centralized pipeline development ### How to choose an ETL platform for multi-source data integration? Based on G2 reviews, the best way to choose an ETL platform for multi-source data integration is to look for evidence that users successfully connect databases, SaaS apps, cloud storage, APIs, spreadsheets, and warehouses without heavy custom work. According to verified users, buyers should prioritize broad connector coverage, strong transformation options, scheduling, and reliability once pipelines are live. G2 reviewers mention that teams also care about how easily data can be standardized from fragmented systems into a single reporting or analytics layer. Reviews repeatedly highlight practical concerns such as debugging difficulty, documentation quality, and connector maturity, especially for edge cases. A strong fit is usually a platform that reduces manual exports, centralizes data movement, and keeps downstream reporting consistent. ### Where to buy ETL tools with flexible pricing for startups and enterprises? Based on G2 reviews, buyers looking for ETL tools with flexible pricing should compare platforms on how predictable costs remain as usage grows, not just on entry price. According to verified users, some tools are valued because they avoid forcing separate purchases for every workflow, while others are praised for fair monthly pricing, startup-friendly plans, or capacity-based structures that make budgeting easier. G2 reviewers mention that pricing friction often appears when usage scales, connectors are gated, or cost models become hard to forecast. For startup and enterprise buyers alike, the practical signal is whether teams feel they can expand integrations without constant pricing surprises. Reviews suggest prioritizing platforms described as affordable, transparent, or cost-effective for real production use. **Here are some of the top-rated products on G2:** - [Skyvia](https://www.g2.com/products/skyvia/reviews) – favored by small and mid-sized teams for affordable no-code integrations and predictable data movement workflows - [Fivetran](https://www.g2.com/products/fivetran/reviews) – chosen for managed connector setup and reliability, though reviews often discuss cost planning as volume grows - [Celigo](https://www.g2.com/products/celigo/reviews) – used for expanding business integrations with low-code flows and reusable templates across systems ### Where to find cloud-native ETL platforms for modern data stacks? Based on G2 reviews, cloud-native ETL platforms for modern data stacks are typically the ones users describe as serverless, easy to integrate with cloud warehouses and storage, and well suited for SaaS-heavy environments. According to verified users, these products often support automated syncing into tools like Snowflake, BigQuery, Redshift, or cloud lakehouse environments while reducing infrastructure management. G2 reviewers mention that buyers should look for platforms praised for quick deployment, broad cloud connectors, scheduling, and compatibility with modern analytics workflows. Reviews also show that the best cloud-native fit depends on whether your team prioritizes low maintenance, open-source flexibility, or warehouse-centric transformation. In practice, users favor platforms that shorten setup time and keep pipelines dependable at scale. ### Which ETL tools support real-time streaming data processing? Based on G2 reviews, Databricks is the clearest match for ETL buyers who need support for real-time or near real-time data processing. According to verified users, Databricks is repeatedly used for streaming alongside batch workloads, with reviewers highlighting scalable Spark-based processing, unified pipeline management, and strong support for handling large or continuously changing datasets. G2 reviewers mention that the platform helps teams bring ETL, analytics, and data engineering into one environment, which is valuable when streaming workflows need to feed downstream reporting or operational systems. Reviewers also note tradeoffs such as cluster startup delays, debugging complexity, and cost monitoring requirements, but recent review volume still makes Databricks the strongest single-winner answer here. **Here are some of the top-rated products on G2:** - [Databricks](https://www.g2.com/products/databricks/reviews) – used for both batch and real-time workflows, scalable Spark processing, and unified ETL plus analytics pipelines ### What best ETL software for building scalable data pipelines? Based on G2 reviews, the strongest ETL software for scalable data pipelines is usually the one users trust for large workloads, multi-source ingestion, and long-running production workflows without constant manual fixes. According to verified users, common strengths include handling high data volumes, integrating cloud services and warehouses, automating scheduling, and supporting reusable pipeline logic. G2 reviewers mention that scalability is not just raw performance; it also depends on monitoring, governance, ease of updates, and whether teams can keep pipelines maintainable as usage grows. Reviews consistently call out Databricks, Fivetran, and FME Platform as examples of tools used for scalable pipelines, though buyers should compare complexity, connector depth, and cost discipline against their own environment. **Here are some of the top-rated products on G2:** - [Databricks](https://www.g2.com/products/databricks/reviews) – used for scalable Spark-based pipelines, unified ETL workflows, and high-volume analytics processing - [Fivetran](https://www.g2.com/products/fivetran/reviews) – used for managed ingestion pipelines from many SaaS sources into cloud warehouses with low maintenance - [FME Platform](https://www.g2.com/products/fme-platform/reviews) – used for large multi-format workflows, automated transformations, and reliable enterprise-scale data movement ### Who offers ETL tools with low-code interface and drag-and-drop builders? Based on G2 reviews, several ETL vendors offer low-code interfaces and drag-and-drop builders aimed at making integration work easier for both technical and less technical teams. According to verified users, these tools are especially valued when they reduce scripting needs, speed up pipeline creation, and make workflows easier to explain or maintain. G2 reviewers mention visual builders, reusable templates, and no-code automation as recurring strengths across multiple products. At the same time, reviews show that low-code does not always mean simple at scale, since debugging, customization, or advanced logic can still introduce complexity. Buyers should look for products whose reviews specifically mention intuitive workflow design, easier onboarding, and broad integration support. **Here are some of the top-rated products on G2:** - [FME Platform](https://www.g2.com/products/fme-platform/reviews) – used for visual workflow building, drag-and-drop transformations, and automation across many systems and formats - [Workato](https://www.g2.com/products/workato/reviews) – used for low-code recipe building, connector-based integrations, and workflow automation across business apps - [Celigo](https://www.g2.com/products/celigo/reviews) – used for low-code integration flows, prebuilt templates, and automating ERP, ecommerce, and SaaS workflows ### What ETL solutions support automated error handling and retries? Based on G2 reviews, ETL solutions that support automated error handling and retries are usually the ones users describe as reliable in production and strong at surfacing failures before they disrupt downstream reporting. According to verified users, these platforms often include retry logic, monitoring, alerts, or workflow controls that reduce the need for manual intervention. G2 reviewers mention detailed error visibility as a major advantage in products like Celigo, Fivetran, and Workato, especially when teams need to manage frequent integrations across multiple systems. Reviews also note that not every product is equally transparent when something breaks, so buyers should look beyond automation claims and evaluate how easy it is to identify, retry, and resolve failures in real workflows. ### Which ETL tools integrate with popular data lakes and data warehouses? Based on G2 reviews, Databricks is the strongest single answer for ETL tools that integrate with popular data lakes and data warehouses. According to verified users, Databricks is repeatedly used in environments that combine lakehouse architecture, cloud storage, external warehouses, and downstream analytics tools. G2 reviewers mention integrations with platforms such as BigQuery, Snowflake, cloud ecosystems, BI tools, and governed data layers, all within a unified workflow for ETL, analytics, and machine learning. Reviewers also highlight that the platform reduces fragmentation by bringing multiple workloads into one environment, though they note that cost management and complexity still require attention. For buyers prioritizing broad lake and warehouse alignment, Databricks appears most consistently in recent review evidence. **Here are some of the top-rated products on G2:** - [Databricks](https://www.g2.com/products/databricks/reviews) – used with lakehouse architectures, cloud storage, external warehouses, and BI ecosystems in one ETL environment ## How Many ETL Tools Products Does G2 Track? **Total Products under this Category:** 249 ### Category Stats (Jun 2026) - **Average Rating**: 4.54/5 (↓0.01 vs May 2026) The average rating of products in this category, based on all submitted ratings - **Top Trending Product**: Maia (+1.11%) - Among all products in this category, Maia recorded the largest rating increase compared to last month *Last updated: June 24, 2026* ## How Does G2 Rank ETL Tools Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 19,000+ Authentic Reviews - 249+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## Which ETL Tools Is Best for Your Use Case? - **Leader:** [Databricks](https://www.g2.com/products/databricks/reviews) - **Highest Performer:** [5X](https://www.g2.com/products/5x/reviews) - **Easiest to Use:** [Skyvia](https://www.g2.com/products/skyvia/reviews) - **Top Trending:** [Matia](https://www.g2.com/products/matia/reviews) - **Best Free Software:** [Fivetran](https://www.g2.com/products/fivetran/reviews) --- **Sponsored** ### Cloudera Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. 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[Databricks](https://www.g2.com/products/databricks/reviews) Databricks is a unified data and AI platform that helps organizations build, govern and scale data pipelines, analytics, machine learning, AI applications and agents. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on Databricks to work with enterprise data and AI at scale. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase, Genie and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value. **Average Rating:** 4.6/5.0 **Total Reviews:** 1,284 **How Do G2 Users Rate Databricks?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.1/10) - **Automation:** 9.1/10 (Category avg: 9.0/10) - **Scalability:** 9.2/10 (Category avg: 8.7/10) - **Auditing:** 8.5/10 (Category avg: 8.1/10) **Who Is the Company Behind Databricks?** - **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc) - **Company Website:** https://databricks.com - **Year Founded:** 2013 - **HQ Location:** San Francisco, CA - **Twitter:** @databricks (92,269 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3477522/ (15,627 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Financial Services - **Company Size:** 48% Enterprise, 38% Mid-Market #### What Are Databricks's Pros and Cons? **Pros:** - Features (288 reviews) - Ease of Use (278 reviews) - Integrations (189 reviews) - Collaboration (150 reviews) - Data Management (150 reviews) **Cons:** - Learning Curve (112 reviews) - Expensive (97 reviews) - Steep Learning Curve (96 reviews) - Missing Features (69 reviews) - Complexity (64 reviews) ### What Do G2 Reviewers Say About Databricks? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **seamless integration** of Databricks with AWS and its powerful features for data management and security. - Users find Databricks to offer **exceptional ease of use** , making data integration and management seamless and efficient. - Users praise the **seamless integration** of Databricks with AWS and Azure, enhancing collaboration and efficiency in data management. - Users appreciate the **excellent collaboration** in Databricks, facilitating real-time teamwork for data engineers and analysts. - Users value the **effective data management features** of Databricks, enhancing usability and decision-making with integrated tools. **Cons:** - Users face a **steep learning curve** with Databricks, complicating initial adoption and resource management. - Users find the **costs to be high** for Databricks, especially when dealing with large data sets. - Users face a **steep learning curve** with Databricks, making initial adoption challenging and requiring specialized support. - Users are disappointed by the **missing features** in Databricks, limiting customization and complicating development processes. - Users find the **complexity** of Databricks challenging due to steep learning curves and integration limitations. #### What Are Recent G2 Reviews of Databricks? **"[Great Spark Scaling, But Slow Cluster Boot Times](https://www.g2.com/survey_responses/databricks-review-12905667)"** **Rating:** 5.0/5.0 stars *— Raj P.* [Read full review](https://www.g2.com/survey_responses/databricks-review-12905667) --- **"[Powerful Lakehouse for Big Data, Collaboration, and Efficient Pipelines](https://www.g2.com/survey_responses/databricks-review-12946286)"** **Rating:** 4.5/5.0 stars *— Konjengbam M.* [Read full review](https://www.g2.com/survey_responses/databricks-review-12946286) --- #### What Are G2 Users Discussing About Databricks? - [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments - [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments - [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 2 upvotes - [What are the features of Databricks?](https://www.g2.com/discussions/what-are-the-features-of-databricks) - 4 comments, 2 upvotes ### 2. [Celigo](https://www.g2.com/products/celigo/reviews) Celigo is the intelligent automation platform built for the AI era. An enterprise-ready iPaaS, Celigo helps organizations unify applications, automate complex operations, and scale digital ecosystems. The platform supports cloud integration, SaaS integration, enterprise application integration, and agentic automation under a single governance model. The platform is accessible to both business teams and developers — anyone can build, configure, and maintain integrations through natural language, while technical teams retain full control over architecture, security, and extensibility. Through an extensive library of 1,000+ prebuilt connectors, organizations can rapidly integrate systems such as ERP, CRM, ecommerce, finance, and support platforms — including NetSuite, Salesforce, SAP, Microsoft Dynamics, and Shopify — while maintaining flexibility for custom integrations and advanced API management. Celigo supports a wide range of enterprise integration scenarios including ERP integration, CRM integration, B2B integration, and EDI (electronic data interchange) workflows. These capabilities allow organizations to streamline supplier, partner, and customer data exchange while ensuring reliable data integration across internal and external systems. Built-in tools for data mapping, data transformation, and data synchronization ensure that information moves accurately and consistently between applications. What sets Celigo apart is its ability to span the full spectrum of automation — from deterministic, rules-based workflows to AI-driven decision-making — without requiring separate platforms or governance models. Celigo Agent Builder enables teams to create AI agents that reason and act across enterprise systems, with configurable guardrails that enforce business policy at runtime. Human-in-the-loop approvals ensure sensitive actions require explicit authorization before execution, and complete audit trails support compliance across every AI interaction. Celigo's MCP Server exposes enterprise capabilities through the Model Context Protocol, giving any AI agent — built inside Celigo or externally — secure, governed, auditable access to the full enterprise tech stack. This makes Celigo a foundational layer for enterprise AI orchestration, enabling organizations to connect external agents to internal systems without sacrificing control or visibility. Celigo Ora, the platform's natural language interface, makes the entire platform accessible through conversation. Anyone — including business teams without technical training — can build, modify, troubleshoot, and maintain integrations and automations by describing what they need in plain language. This eliminates the specialist bottleneck not just for building automations, but for ongoing maintenance and issue resolution as well. To accelerate deployment, Celigo offers fully managed Integration Apps and reusable integration templates that simplify common use cases such as order-to-cash automation, ecommerce integrations, and financial data flows. Centralized monitoring, runtime governance controls, and scalable architecture give enterprises full visibility into integration and automation processes while maintaining reliability and compliance. Designed for modern IT and operations teams, Celigo empowers enterprises to unify integration, automation, and AI on a single platform — scaling capacity without scaling headcount, and building a durable foundation for digital transformation across the entire application landscape. **Average Rating:** 4.6/5.0 **Total Reviews:** 1,018 **How Do G2 Users Rate Celigo?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.1/10) - **Automation:** 10.0/10 (Category avg: 9.0/10) - **Scalability:** 10.0/10 (Category avg: 8.7/10) **Who Is the Company Behind Celigo?** - **Seller:** [Celigo](https://www.g2.com/sellers/celigo) - **Company Website:** https://www.celigo.com - **Year Founded:** 2011 - **HQ Location:** Redwood City, California - **Twitter:** @celigoinc (1,418 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/275831/ (766 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** NetSuite Administrator, IT Manager - **Top Industries:** Retail, Computer Software - **Company Size:** 58% Mid-Market, 37% Small-Business #### What Are Celigo's Pros and Cons? **Pros:** - Ease of Use (469 reviews) - Integrations (297 reviews) - Integration Capabilities (285 reviews) - Easy Integrations (252 reviews) - Customer Support (220 reviews) **Cons:** - Error Handling (107 reviews) - Expensive (95 reviews) - Learning Curve (91 reviews) - Complexity (69 reviews) - Pricing Issues (69 reviews) ### What Do G2 Reviewers Say About Celigo? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **user-friendly UI** of Celigo, enhancing ease of integration and management for all skill levels. - Users praise Celigo for its **user-friendly integrations** , enabling customizable solutions that effectively meet evolving business needs. - Users appreciate the **integration capabilities** of Celigo, enabling effortless connections and simplifying complex tasks. - Users praise the **easy integrations** with Celigo, facilitating seamless connections and simplifying workflows across systems. - Users value the **helpful and thorough customer support** provided by Celigo, enhancing their customization experience. **Cons:** - Users find **error handling challenging** , with unclear messages and random issues complicating the resolution process. - Users note the **high cost** of Celigo, with significant increases as additional features are added. - Users often face a steep **learning curve** with Celigo, making initial navigation and understanding challenging. - Users experience **complexity in debugging** and system limitations, making integrations more challenging than anticipated. - Users express concerns about **premium pricing** and unexpected cost increases, though see value in the product. #### What Are Recent G2 Reviews of Celigo? **"[Celigo, a greta integrator with a University Lab inside it.](https://www.g2.com/survey_responses/celigo-review-10532295)"** **Rating:** 5.0/5.0 stars *— Ignacio R.* [Read full review](https://www.g2.com/survey_responses/celigo-review-10532295) --- **"[Go for it if you’re looking for a solid integration platform](https://www.g2.com/survey_responses/celigo-review-11876505)"** **Rating:** 4.5/5.0 stars *— Goutham P.* [Read full review](https://www.g2.com/survey_responses/celigo-review-11876505) --- #### What Are G2 Users Discussing About Celigo? - [What is Celigo used for?](https://www.g2.com/discussions/what-is-celigo-used-for) ### 3. [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Store 10 GiB of data and run up to 1 TiB of queries for free per month. **Average Rating:** 4.5/5.0 **Total Reviews:** 1,147 **How Do G2 Users Rate Google Cloud BigQuery?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10) - **Automation:** 8.8/10 (Category avg: 9.0/10) - **Scalability:** 9.3/10 (Category avg: 8.7/10) - **Auditing:** 8.3/10 (Category avg: 8.1/10) **Who Is the Company Behind Google Cloud BigQuery?** - **Seller:** [Google](https://www.g2.com/sellers/google) - **Year Founded:** 1998 - **HQ Location:** Mountain View, CA - **Twitter:** @google (31,899,995 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1441/ (341,888 employees on LinkedIn®) - **Ownership:** NASDAQ:GOOG **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 38% Enterprise, 35% Mid-Market #### What Are Google Cloud BigQuery's Pros and Cons? **Pros:** - Ease of Use (129 reviews) - Speed (126 reviews) - Integrations (110 reviews) - Fast Querying (105 reviews) - Query Efficiency (100 reviews) **Cons:** - Expensive (112 reviews) - Query Issues (65 reviews) - Cost Management (52 reviews) - Cost Issues (51 reviews) - Learning Curve (49 reviews) ### What Do G2 Reviewers Say About Google Cloud BigQuery? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Google Cloud BigQuery, enabling fast data analysis without infrastructure hassles. - Users appreciate the **fast processing speed** of BigQuery, enabling effortless handling of large datasets with ease. - Users value the **seamless integration** with Google Cloud services, enhancing their data processing and analytics capabilities. - Users appreciate the **fast querying capabilities** of Google Cloud BigQuery, enabling efficient analysis of massive datasets effortlessly. - Users appreciate the **query efficiency** of BigQuery, finding it easy to handle large datasets with speed and scalability. **Cons:** - Users find the **cost structure expensive** , especially when executing complex queries due to data scanning charges. - Users struggle with **query issues** in BigQuery, leading to unexpected costs and challenges in optimization and management. - Users face **unpredictable pricing** with Google Cloud BigQuery, often leading to unexpectedly high bills and management challenges. - Users face **cost issues** with BigQuery, as bills can escalate unexpectedly without proper management and optimization. - Users find the **steep learning curve** of Google Cloud BigQuery challenging, hindering their ability to utilize advanced features effectively. #### What Are Recent G2 Reviews of Google Cloud BigQuery? **"[Easy-to-Use Cloud Tool with Shareable, Saved Queries](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)"** **Rating:** 4.0/5.0 stars *— Reetika P.* [Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418) --- **"[Scalable, Secure BigQuery That Connects Seamlessly Across Services](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)"** **Rating:** 5.0/5.0 stars *— Aayush M.* [Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747) --- #### What Are G2 Users Discussing About Google Cloud BigQuery? - [Is Big Query free?](https://www.g2.com/discussions/is-big-query-free) - 3 comments, 1 upvote - [Is BigQuery part of Google Cloud Platform?](https://www.g2.com/discussions/is-bigquery-part-of-google-cloud-platform) - 2 comments, 2 upvotes - [What is Google BigQuery based on?](https://www.g2.com/discussions/what-is-google-bigquery-based-on) - 1 comment - [What is Google BigQuery used for?](https://www.g2.com/discussions/what-is-google-bigquery-used-for) - 1 comment ### 4. [Alteryx](https://www.g2.com/products/alteryx/reviews) Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. **Average Rating:** 4.6/5.0 **Total Reviews:** 822 **How Do G2 Users Rate Alteryx?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.1/10) - **Automation:** 9.7/10 (Category avg: 9.0/10) - **Scalability:** 10.0/10 (Category avg: 8.7/10) - **Auditing:** 10.0/10 (Category avg: 8.1/10) **Who Is the Company Behind Alteryx?** - **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx) - **Company Website:** https://www.alteryx.com - **Year Founded:** 1997 - **HQ Location:** Irvine, CA - **Twitter:** @alteryx (26,149 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,304 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Analyst - **Top Industries:** Financial Services, Accounting - **Company Size:** 63% Enterprise, 21% Mid-Market #### What Are Alteryx's Pros and Cons? **Pros:** - Ease of Use (333 reviews) - Automation (148 reviews) - Intuitive (132 reviews) - Easy Learning (102 reviews) - Efficiency (102 reviews) **Cons:** - Expensive (88 reviews) - Learning Curve (80 reviews) - Missing Features (62 reviews) - Learning Difficulty (55 reviews) - Slow Performance (41 reviews) ### What Do G2 Reviewers Say About Alteryx? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Alteryx, finding it simple to automate complex tasks through drag and drop. - Users appreciate Alteryx for its **automation capabilities** , enhancing data handling efficiency and enabling deeper analytical insights. - Users find Alteryx to be **very intuitive** , making it easy for non-technical individuals to learn and use effectively. - Users find that Alteryx offers **easy learning** , making technology accessible for non-technical individuals through intuitive design. - Users commend Alteryx for its **high efficiency** in managing data, streamlining workflows and saving valuable time. **Cons:** - Users find the **license cost to be expensive** , making it challenging for small teams and startups to justify. - Users face a **learning curve** that can hinder beginners as they explore Alteryx's advanced features effectively. - Users find **missing features** in Alteryx, such as limited reporting and absence of Mac compatibility, frustrating. - Users note the **steep learning curve** of Alteryx, especially for those familiar with SQL and RegEx. - Users report **slow performance** with Alteryx, particularly when handling large workflows, causing significant analysis delays. #### What Are Recent G2 Reviews of Alteryx? **"[Intuitive Drag-and-Drop Analytics That Speeds Up Data Prep and Insights](https://www.g2.com/survey_responses/alteryx-review-12983224)"** **Rating:** 4.5/5.0 stars *— Akhil S.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-12983224) --- **"[Alteryx Streamlines Data Prep with an Intuitive Drag-and-Drop Workflow Builder](https://www.g2.com/survey_responses/alteryx-review-13000974)"** **Rating:** 4.5/5.0 stars *— Ankit K.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-13000974) --- ### 5. [IBM watsonx.data](https://www.g2.com/products/ibm-watsonx-data/reviews) IBM® watsonx.data® helps you access, integrate and understand all your data —structured and unstructured—across any environment. It optimizes workloads for price and performance while enforcing consistent governance across sources, formats and teams. Watch the demo to learn how watsonx.data empowers you to build gen AI apps and powerful AI agents. Free Trial available: https://ibm.biz/Watsonx-data\_Trial **Average Rating:** 4.4/5.0 **Total Reviews:** 159 **How Do G2 Users Rate IBM watsonx.data?** - **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 9.1/10) - **Automation:** 8.3/10 (Category avg: 9.0/10) - **Scalability:** 7.5/10 (Category avg: 8.7/10) - **Auditing:** 5.8/10 (Category avg: 8.1/10) **Who Is the Company Behind IBM watsonx.data?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Company Website:** https://www.ibm.com - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer, CEO - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 34% Small-Business, 32% Enterprise #### What Are IBM watsonx.data's Pros and Cons? **Pros:** - Ease of Use (67 reviews) - Features (47 reviews) - Data Management (41 reviews) - Integrations (33 reviews) - Analytics (31 reviews) **Cons:** - Learning Curve (38 reviews) - Complexity (25 reviews) - Expensive (20 reviews) - Difficult Setup (17 reviews) - Difficulty (17 reviews) ### What Do G2 Reviewers Say About IBM watsonx.data? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of IBM watsonx.data, streamlining data management and enhancing analytical efficiency. - Users appreciate the **fast and easy data management** of IBM watsonx.data, enhancing efficiency with effective query execution. - Users appreciate the **flexibility and governance** of IBM watsonx.data, enhancing data management across hybrid environments. - Users appreciate the **seamless integration with other IBM tools** , enhancing workflow and efficiency in data management. - Users laud the **streamlined analytics** and unified lakehouse capabilities of IBM watsonx.data for efficient data management. **Cons:** - Users face a **steep learning curve** with watsonx.data, making initial setup and feature mastery challenging. - Users find the **complexity** of watsonx.data challenging, especially for beginners and during the setup process. - Users find the **pricing to be quite high** , making it challenging for small teams to justify investment in the product. - Users face a **difficult setup** with IBM watsonx.data, requiring careful configuration and facing a steep learning curve. - Users report experiencing **significant difficulties** with documentation and navigation, making it less beginner-friendly. #### What Are Recent G2 Reviews of IBM watsonx.data? **"[Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)"** **Rating:** 4.0/5.0 stars *— Arkajit D.* [Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202) --- **"[Unified Data Management with Learning Curve](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742)"** **Rating:** 5.0/5.0 stars *— Anchal P.* [Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742) --- ### 6. [FME Platform](https://www.g2.com/products/fme-platform/reviews) FME, made by Safe Software, is the only All-Data, Any-AI Enterprise Integration Platform connecting all your data, applications, and AI services. All Data Velocities - Whether it’s batch, event, or stream processing, FME delivers you no-code business orchestration and automation. All Data Locations - Wherever your data is - in the cloud, on-premises, or both - FME matches your data landscape with processing, increasing scalability, agility, and security. All Data Types - From databases to business systems to IoT, you name it, we connect it. As the only integration platform with support for spatial data, FME delivers new insights so you can make better decisions and stay ahead of the competition. Any AI Technology - Power your workflows with the right data at the right time regardless of modality, location or data velocity. FME powers real-time, context-aware automation, scaling AI where and how you need it. **Average Rating:** 4.6/5.0 **Total Reviews:** 124 **How Do G2 Users Rate FME Platform?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10) - **Automation:** 9.4/10 (Category avg: 9.0/10) - **Scalability:** 8.2/10 (Category avg: 8.7/10) - **Auditing:** 8.9/10 (Category avg: 8.1/10) **Who Is the Company Behind FME Platform?** - **Seller:** [Safe Software](https://www.g2.com/sellers/safe-software) - **Company Website:** https://fme.safe.com/ - **Year Founded:** 1993 - **HQ Location:** British Columbia, Canada - **Twitter:** @SafeSoftware (4,972 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/50027/ (342 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** GIS Analyst, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 50% Mid-Market, 29% Small-Business #### What Are FME Platform's Pros and Cons? **Pros:** - Ease of Use (33 reviews) - Data Management (19 reviews) - Automation (18 reviews) - Features (16 reviews) - Data Transformation (15 reviews) **Cons:** - Complexity (10 reviews) - Expensive (10 reviews) - Learning Curve (7 reviews) - Difficult Learning (6 reviews) - Pricing Issues (6 reviews) ### What Do G2 Reviewers Say About FME Platform? *AI-generated summary from verified user reviews* **Pros:** - Users find FME Platform's **ease of use** exceptional, empowering both beginners and experts to create workflows effortlessly. - Users love the **wide range of data handling options** in FME Platform, enhancing workflows through seamless integration and automation. - Users value the **automation capabilities** of FME Platform, streamlining repetitive tasks and enhancing overall workflow efficiency. - Users value the **intuitive ease of use** and extensive library of supported data types in FME Platform. - Users are impressed by FME Platform's **versatile data transformation capabilities** , enabling seamless integration and quick setup for ETL tasks. **Cons:** - Users find the **complexity of authentication and administration tools** in FME Platform frustrating and cumbersome to navigate. - Users find FME Platform to be **expensive** , creating difficulties for smaller teams and individual users to justify investment. - Users find the **learning curve steep** , making it difficult for new users to effectively utilize the FME Platform. - Users note a **difficult learning curve** , finding initial usage challenging before it improves with experience. - Users express concerns about **pricing issues** , feeling that recent changes make FME less accessible for smaller teams. #### What Are Recent G2 Reviews of FME Platform? **"[FME Saves Time with Powerful GIS ETL and Automation](https://www.g2.com/survey_responses/fme-platform-review-12863747)"** **Rating:** 4.5/5.0 stars *— Denise G.* [Read full review](https://www.g2.com/survey_responses/fme-platform-review-12863747) --- **"[Reliable Enablement Platform for Learning, APIs, and Secure Workflows](https://www.g2.com/survey_responses/fme-platform-review-12832718)"** **Rating:** 4.5/5.0 stars *— Drew M.* [Read full review](https://www.g2.com/survey_responses/fme-platform-review-12832718) --- #### What Are G2 Users Discussing About FME Platform? - [What does FME stand for in FME Server?](https://www.g2.com/discussions/what-does-fme-stand-for-in-fme-server) - [Is FME an ETL?](https://www.g2.com/discussions/is-fme-an-etl) - [What is FME process?](https://www.g2.com/discussions/what-is-fme-process) - [What is FME software used for?](https://www.g2.com/discussions/what-is-fme-software-used-for) ### 7. [Fivetran](https://www.g2.com/products/fivetran/reviews) Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights. **Average Rating:** 4.3/5.0 **Total Reviews:** 782 **How Do G2 Users Rate Fivetran?** - **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 9.1/10) - **Automation:** 9.0/10 (Category avg: 9.0/10) - **Scalability:** 8.5/10 (Category avg: 8.7/10) - **Auditing:** 7.4/10 (Category avg: 8.1/10) **Who Is the Company Behind Fivetran?** - **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran) - **Company Website:** https://www.fivetran.com/ - **Year Founded:** 2012 - **HQ Location:** Oakland, CA - **Twitter:** @fivetran (5,767 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,848 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 59% Mid-Market, 28% Small-Business #### What Are Fivetran's Pros and Cons? **Pros:** - Ease of Use (187 reviews) - Easy Setup (74 reviews) - Easy Integration (73 reviews) - Customer Support (62 reviews) - User Interface (59 reviews) **Cons:** - Sync Issues (60 reviews) - Expensive (36 reviews) - Integration Issues (28 reviews) - Learning Curve (27 reviews) - Pricing Issues (24 reviews) ### What Do G2 Reviewers Say About Fivetran? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Fivetran, finding it simple to integrate and maintain with impressive ROI. - Users find Fivetran's **easy setup** very convenient, supporting their current applications effortlessly. - Users appreciate the **easy integration** of Fivetran, enabling seamless connection with various applications and streamlined data access. - Users value the **responsive customer support** of Fivetran, finding it helpful and easy to work with. - Users appreciate the **intuitive and simple layout** of Fivetran, enhancing their data integration experience. **Cons:** - Users face **sync issues** with sporadic failures and conflicts with dbt dependencies, complicating their workflow. - Users find Fivetran's pricing to be **quite expensive** , limiting accessibility and practicality for wider usage. - Users face **integration issues** with Fivetran, particularly around schema ownership and modifying existing connections. - Users find the **learning curve steep** , requiring technical knowledge to manage complex queries effectively. - Users find Fivetran's **pricing issues** to be expensive and impractical, limiting broader accessibility and usage. #### What Are Recent G2 Reviews of Fivetran? **"[Simple Setup, Reliable Syncing, and Powerful Pre-Built Connectors](https://www.g2.com/survey_responses/fivetran-review-12945842)"** **Rating:** 4.5/5.0 stars *— Luciana S.* [Read full review](https://www.g2.com/survey_responses/fivetran-review-12945842) --- **"[Trouble-Free Data Pipelines with Effortless Connections to Nearly Every Service](https://www.g2.com/survey_responses/fivetran-review-12999542)"** **Rating:** 5.0/5.0 stars *— Verified User in Insurance* [Read full review](https://www.g2.com/survey_responses/fivetran-review-12999542) --- #### What Are G2 Users Discussing About Fivetran? - [What is Fivetran used for?](https://www.g2.com/discussions/fivetran-what-is-fivetran-used-for) - 1 comment - [What is Census used for?](https://www.g2.com/discussions/what-is-census-used-for) - [Who owns Fivetran?](https://www.g2.com/discussions/who-owns-fivetran) - [How much does Fivetran cost?](https://www.g2.com/discussions/how-much-does-fivetran-cost) - 1 comment - [Is Fivetran an ETL tool?](https://www.g2.com/discussions/is-fivetran-an-etl-tool) - 2 comments ### 8. [Domo](https://www.g2.com/products/domo/reviews) Domo's AI and Data Products Platform empowers organizations to turn data into actionable insights and solutions. It allows users to seamlessly connect diverse data sources, prepare data for use, and generate dynamic reports and visualizations—all within a single interface. With built-in AI and automation capabilities, teams can easily build and use AI agents, streamline workflows, and create tailored solutions. **Average Rating:** 4.3/5.0 **Total Reviews:** 994 **How Do G2 Users Rate Domo?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10) - **Automation:** 8.5/10 (Category avg: 9.0/10) - **Scalability:** 7.9/10 (Category avg: 8.7/10) - **Auditing:** 7.2/10 (Category avg: 8.1/10) **Who Is the Company Behind Domo?** - **Seller:** [Domo](https://www.g2.com/sellers/domo) - **Company Website:** https://www.domo.com - **Year Founded:** 2010 - **HQ Location:** American Fork, UT - **Twitter:** @Domotalk (63,513 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/25237/ (1,305 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Business Analyst - **Top Industries:** Computer Software, Marketing and Advertising - **Company Size:** 49% Mid-Market, 29% Enterprise #### What Are Domo's Pros and Cons? **Pros:** - Ease of Use (247 reviews) - Data Visualization (116 reviews) - Intuitive (95 reviews) - Easy Integrations (92 reviews) - Integrations (88 reviews) **Cons:** - Learning Curve (66 reviews) - Missing Features (59 reviews) - Data Management Issues (55 reviews) - Expensive (44 reviews) - Complexity (43 reviews) ### What Do G2 Reviewers Say About Domo? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **user-friendly interface** of Domo, enhancing accessibility for both tech-savvy and non-tech-savvy individuals. - Users value the **user-friendly data visualization** features of Domo, enabling effortless graph creation and real-time tracking. - Users highlight Domo's **intuitive design** , making data management accessible for all, even non-tech-savvy individuals. - Users appreciate the **easy integrations** in Domo, enabling seamless data handling from multiple sources for informed decisions. - Users value Domo's **seamless integration** with various data sources, enhancing efficiency and collaboration in data management. **Cons:** - Users find the **learning curve steep** , struggling to keep up with updates and manage functionality challenges effectively. - Users express frustration over **missing features** in Domo, such as dynamic columns and a confusing consumption model. - Users face **data management issues** with Domo, citing unreliable connectors and challenges in reporting and functionality. - Users find Domo's pricing to be **unreasonably expensive** , causing dissatisfaction and trust issues over sudden cost increases. - Users find Domo's **complexity** frustrating due to rigid datasets and cumbersome dashboard management. #### What Are Recent G2 Reviews of Domo? **"[Interactive Real-Time Dashboards That Make Complex Data Easy](https://www.g2.com/survey_responses/domo-review-13003120)"** **Rating:** 5.0/5.0 stars *— Anil B.* [Read full review](https://www.g2.com/survey_responses/domo-review-13003120) --- **"[All-in-One Platform for Real-Time Analytics and Dashboards](https://www.g2.com/survey_responses/domo-review-12676104)"** **Rating:** 5.0/5.0 stars *— Anuj T.* [Read full review](https://www.g2.com/survey_responses/domo-review-12676104) --- #### What Are G2 Users Discussing About Domo? - [What is Domo used for?](https://www.g2.com/discussions/what-is-domo-used-for) - 1 comment - [How much does Domo cost?](https://www.g2.com/discussions/how-much-does-domo-cost) - [What is Domo data?](https://www.g2.com/discussions/what-is-domo-data) - [Is Domo any good?](https://www.g2.com/discussions/is-domo-any-good) - [What does Domo software do?](https://www.g2.com/discussions/what-does-domo-software-do) ### 9. [Workato](https://www.g2.com/products/workato/reviews) Workato is the #1-rated iPaaS and the leader in Enterprise MCP — the platform enterprises trust to unify integration, automation, and AI in one secure, cloud-native runtime. Trusted by over 12,000 customers including half the Fortune 500, Workato connects every system, process, and data source with 14,000+ pre-built connectors. What sets Workato apart: Enterprise MCP turns proven business processes into governed, agent-ready skills that any AI agent — Claude, ChatGPT, Cursor, or custom-built — can execute safely and predictably. No rip-and-replace required. Whether modernizing legacy integrations or deploying agentic AI at scale, Workato delivers the orchestration, governance, and trust needed in the enterprise. **Average Rating:** 4.7/5.0 **Total Reviews:** 749 **How Do G2 Users Rate Workato?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10) - **Automation:** 9.2/10 (Category avg: 9.0/10) - **Scalability:** 9.0/10 (Category avg: 8.7/10) - **Auditing:** 8.3/10 (Category avg: 8.1/10) **Who Is the Company Behind Workato?** - **Seller:** [Workato](https://www.g2.com/sellers/workato) - **Company Website:** https://www.workato.com - **Year Founded:** 2013 - **HQ Location:** Mountain View, California - **Twitter:** @Workato (3,641 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3675685 (1,401 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer, Senior Software Engineer - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 43% Mid-Market, 33% Enterprise #### What Are Workato's Pros and Cons? **Pros:** - Ease of Use (240 reviews) - Easy Integrations (232 reviews) - Integrations (171 reviews) - Features (156 reviews) - Automation (149 reviews) **Cons:** - Learning Curve (77 reviews) - Complexity (70 reviews) - Data Limitations (55 reviews) - Missing Features (55 reviews) - Steep Learning Curve (48 reviews) ### What Do G2 Reviewers Say About Workato? *AI-generated summary from verified user reviews* **Pros:** - Users find Workato's **ease of use** exceptional, enabling swift automation without requiring technical expertise. - Users appreciate the **easy integrations** in Workato, enabling seamless automation between their favorite tools like Salesforce and Slack. - Users value the **ease of integrating applications** with Workato, enabling efficient automation without technical expertise. - Users appreciate the **user-friendly low-code interface** of Workato, which facilitates seamless automation and integration across systems. - Users love the **ease of automation** with Workato, simplifying integrations and saving valuable time on repetitive tasks. **Cons:** - Users note a **steep learning curve** with Workato, requiring time and practice to effectively utilize its features. - Users find Workato's **complexity** overwhelming, especially regarding terminology and pricing, complicating the onboarding experience. - Users find **data limitations** in Workato restrictive, hindering extensive use and complicating debugging and file transfers. - Users are frustrated with the **limited application coverage** in Workato, requiring manual setups for some integrations. - Users find the **steep learning curve** of Workato challenging, especially during initial onboarding and for beginners. #### What Are Recent G2 Reviews of Workato? **"[Workato helps us building complex integrations at lightning speed.](https://www.g2.com/survey_responses/workato-review-10305521)"** **Rating:** 5.0/5.0 stars *— Sreenath B.* [Read full review](https://www.g2.com/survey_responses/workato-review-10305521) --- **"[The Platform That Grew With Us](https://www.g2.com/survey_responses/workato-review-12941177)"** **Rating:** 5.0/5.0 stars *— Anshu b.* [Read full review](https://www.g2.com/survey_responses/workato-review-12941177) --- #### What Are G2 Users Discussing About Workato? - [What does Workato do?](https://www.g2.com/discussions/what-does-workato-do) - [How much does Workato cost?](https://www.g2.com/discussions/how-much-does-workato-cost) - 1 comment - [What is a Workato recipe?](https://www.g2.com/discussions/what-is-a-workato-recipe) - 3 comments - [What is Workato used for?](https://www.g2.com/discussions/what-is-workato-used-for) ### 10. [Skyvia](https://www.g2.com/products/skyvia/reviews) Skyvia is a no-code cloud data integration and data pipeline platform that enables ETL, ELT, Reverse ETL, data migration, one-way and bi-directional data sync, workflow automation, real-time connectivity, and much more. Benefits of Using Skyvia: • Cost efficiency: With affordable, flexible pricing plans for each product, Skyvia suites for businesses of any size. • Ease of Use: Based on extensive customer feedback, ease of use is Skyvia's strongest quality. • Flexibility: Skyvia provides adaptable, no-code integration tools for both basic and advanced business scenarios. • Trust: Skyvia is trusted by thousands of data-driven organizations around the globe. With a vast library of 200+ connectors, Skyvia provides seamless integration among various cloud applications, databases, and data warehouses, including Salesforce, Dynamics CRM, QuickBooks Online, SQL Server, Amazon Redshift, Google BigQuery, and others. **Average Rating:** 4.8/5.0 **Total Reviews:** 322 **How Do G2 Users Rate Skyvia?** - **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 9.1/10) - **Automation:** 9.4/10 (Category avg: 9.0/10) - **Scalability:** 9.3/10 (Category avg: 8.7/10) - **Auditing:** 9.0/10 (Category avg: 8.1/10) **Who Is the Company Behind Skyvia?** - **Seller:** [Devart](https://www.g2.com/sellers/devart) - **Year Founded:** 1997 - **HQ Location:** Wilmington, Delaware, USA - **Twitter:** @DevartSoftware (1,736 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/800325/ (252 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** CEO, CTO - **Top Industries:** Information Technology and Services, Marketing and Advertising - **Company Size:** 52% Small-Business, 42% Mid-Market #### What Are Skyvia's Pros and Cons? **Pros:** - Ease of Use (46 reviews) - Easy Integrations (33 reviews) - Easy Setup (30 reviews) - Setup Ease (29 reviews) - Integrations (26 reviews) **Cons:** - Information Deficiency (8 reviews) - Difficult Setup (7 reviews) - Learning Curve (7 reviews) - Poor Documentation (7 reviews) - Setup Difficulty (7 reviews) ### What Do G2 Reviewers Say About Skyvia? *AI-generated summary from verified user reviews* **Pros:** - Users love the **intuitive and user-friendly interface** of Skyvia, making integrations a breeze and saving time. - Users value the **easy integrations** of Skyvia, appreciating its intuitive interface and broad range of connections. - Users value the **easy setup** of Skyvia, enabling smooth integration and management of data effortlessly. - Users find the **initial setup easy** , simplifying integration and enhancing overall operational efficiency. - Users value the **easy and efficient integrations** with Skyvia, appreciating its simplicity and advanced functionality. **Cons:** - Users feel there is an **information deficiency** , as documentation and logs lack details for effective troubleshooting. - Users find the **difficult setup** of Skyvia challenging, especially with large datasets and field mapping configurations. - Users find the **learning curve steep** , particularly with complex setups and the dense interface of Skyvia. - Users find the **poor documentation** of Skyvia lacking in real-world examples, complicating integrations and troubleshooting. - Users find the **setup difficulty** with Skyvia challenging, often requiring extra time and configuration for large datasets. #### What Are Recent G2 Reviews of Skyvia? **"[Reliable Data Integration Without the Headache](https://www.g2.com/survey_responses/skyvia-review-12998949)"** **Rating:** 5.0/5.0 stars *— Syed Minhajul I.* [Read full review](https://www.g2.com/survey_responses/skyvia-review-12998949) --- **"[Straightforward, Reliable Data Sync Between Cloud Apps and Databases](https://www.g2.com/survey_responses/skyvia-review-12843850)"** **Rating:** 5.0/5.0 stars *— Marcus W.* [Read full review](https://www.g2.com/survey_responses/skyvia-review-12843850) --- #### What Are G2 Users Discussing About Skyvia? - [What is Skyvia used for?](https://www.g2.com/discussions/what-is-skyvia-used-for) - 1 comment ### 11. [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) The SnapLogic Platform is an agentic integration and automation solution designed to assist enterprise teams in connecting applications, data sources, and APIs while orchestrating AI-powered workflows across both cloud and on-premises environments. Established in 2006 and headquartered in San Mateo, California, SnapLogic serves a diverse range of industries, including financial services, pharmaceuticals, manufacturing, software, and higher education, with a global presence across North America, Europe, and Asia Pacific. Targeted primarily at IT teams, data engineers, and integration specialists, the SnapLogic Platform addresses the critical need for seamless data movement between systems, automation of business processes, and governance of AI agent activities at scale. The platform supports various use cases, including application integration, data pipeline management, API lifecycle management, legacy system modernization, and enterprise AI orchestration. This versatility makes it a valuable tool for organizations looking to enhance their operational efficiency and data accessibility. Key features of the SnapLogic Platform include a visual, low-code pipeline builder that allows teams to create, test, and deploy integrations without the need for extensive coding knowledge. This drag-and-drop designer significantly reduces reliance on developer resources, enabling quicker project turnaround. Additionally, the platform boasts a pre-built Snaps connector library, offering over 1,000 reusable connectors for various enterprise applications, databases, cloud services, and data platforms. This extensive library supports both simple and complex integration patterns, streamlining the integration process. Another notable feature is SnapGPT, an AI co-pilot integrated into the platform that assists users in generating integration pipelines, suggesting data mappings, and troubleshooting issues using natural language inputs. This innovative tool enhances user experience and efficiency, making it easier for teams to navigate the complexities of integration. The platform also includes robust API management tools for creating, publishing, securing, and monitoring APIs, facilitating the exposure and consumption of data services across internal and external systems. Moreover, SnapLogic enables agentic workflow automation, allowing users to design and orchestrate AI agents that execute multi-step business processes. With built-in support for the Model Context Protocol (MCP), organizations can effectively manage agent interactions across various models and tools. The platform also supports data integration and transformation for batch, real-time, and streaming data pipelines, equipped with capabilities for mapping, enrichment, and transformation of both structured and unstructured data. Centralized monitoring and governance features provide a unified dashboard for tracking pipeline performance, managing access controls, and ensuring auditability across all integration and automation activities. The SnapLogic Platform addresses common challenges organizations face when scaling their technology operations: fragmented data across disconnected systems, high integration development costs, and the complexity of deploying AI in regulated or mission-critical environments. By providing a unified platform for both traditional integration and agentic automation, it reduces reliance on custom-coded connectors and enables teams to build and manage integrations without requiring deep software engineering expertise. **Average Rating:** 4.4/5.0 **Total Reviews:** 371 **How Do G2 Users Rate SnapLogic Intelligent Integration Platform (IIP)?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10) - **Automation:** 8.6/10 (Category avg: 9.0/10) - **Scalability:** 8.4/10 (Category avg: 8.7/10) - **Auditing:** 8.1/10 (Category avg: 8.1/10) **Who Is the Company Behind SnapLogic Intelligent Integration Platform (IIP)?** - **Seller:** [SnapLogic](https://www.g2.com/sellers/snaplogic) - **Company Website:** https://www.snaplogic.com - **Year Founded:** 2006 - **HQ Location:** San Mateo, CA - **Twitter:** @SnapLogic (7,348 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/210766/ (317 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Consultant - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 46% Enterprise, 36% Mid-Market #### What Are SnapLogic Intelligent Integration Platform (IIP)'s Pros and Cons? **Pros:** - Ease of Use (77 reviews) - Easy Integrations (62 reviews) - Integrations (48 reviews) - User Interface (47 reviews) - Automation (40 reviews) **Cons:** - Performance Issues (29 reviews) - Technical Difficulties (22 reviews) - Poor Performance (21 reviews) - Complexity (20 reviews) - Error Reporting (20 reviews) ### What Do G2 Reviewers Say About SnapLogic Intelligent Integration Platform (IIP)? *AI-generated summary from verified user reviews* **Pros:** - Users find SnapLogic IIP's **ease of use** invaluable, enabling quick connections and streamlined workflows for various tasks. - Users praise SnapLogic IIP for its **easy integrations** , featuring a user-friendly interface and numerous prebuilt connectors. - Users appreciate the **easy integration with various tools** , enhancing workflow efficiency and simplifying system connectivity. - Users appreciate the **user-friendly interface** of SnapLogic IIP, simplifying complex integrations with a clean drag-and-drop experience. - Users value the **automation capabilities** of SnapLogic IIP, enhancing efficiency and simplifying complex integration tasks. **Cons:** - Users frequently face **performance issues** with SnapLogic, including slow loading times and memory problems with large data sets. - Users face **technical difficulties** with SnapLogic IIP, including challenges with debugging and performance in complex scenarios. - Users report **poor performance** under heavy workloads, facing significant issues with data processing efficiency and debugging. - Users find the **debugging complexity** challenging, which can lead to confusion in using the SnapLogic IIP effectively. - Users find the **error reporting lacking detail** , making troubleshooting and debugging more time-consuming and challenging. #### What Are Recent G2 Reviews of SnapLogic Intelligent Integration Platform (IIP)? **"[Improved Data Connectivity with Room for Stability Enhancements](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-12375834)"** **Rating:** 4.0/5.0 stars *— Savio M.* [Read full review](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-12375834) --- **"[Intuitive Drag-and-Drop Pipelines with Reliable Real-Time Sync](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-12873225)"** **Rating:** 5.0/5.0 stars *— Abhay K.* [Read full review](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-12873225) --- #### What Are G2 Users Discussing About SnapLogic Intelligent Integration Platform (IIP)? - [What is SnapLogic Intelligent Integration Platform (IIP) used for?](https://www.g2.com/discussions/what-is-snaplogic-intelligent-integration-platform-iip-used-for) - 1 comment ### 12. [Boomi Data Integration](https://www.g2.com/products/boomi-data-integration/reviews) Rivery's SaaS platform provides a unified solution for ELT pipelines, workflow orchestration, and data operations. Achieve more with less and create the most efficient, scalable data stack for your organization. Some of Rivery's features and capabilities: - Completely Automated SaaS Platform: Get setup and start connecting data in the Rivery platform in just a few minutes with little to no maintenance required. - Unified Data Ingestion, Transformation, & Orchestration: 100% data source capability, insight-ready data with both SQL and Python transformations, and complete workflow automation. - 200+ Native Connectors: Instantly connect to applications, databases, file storage options, and data warehouses with our fully-managed and always up-to-date connectors, including BigQuery, Redshift, Shopify, Snowflake, Amazon S3, Firebolt, Databricks, Salesforce, MySQL, PostgreSQL, and Rest API to name just a few. - Python Support: Have a data source that requires custom code? With Rivery’s native Python support, you can pull data from any system, no matter how complex the need. - Change Data Capture/Data Replication: Rivery’s best-in-class CDC support provides an easy, reliable and fast solution for replicating data from a database to your data warehouse. - 1-Click Data Apps: With Rivery Kits, deploy complete, production-level workflow templates in minutes with data models, pipelines, transformations, table schemas, and orchestration logic already defined for you based on best practices. - Data Development Lifecycle Support: Separate walled-off environments for each stage of your development, from dev and staging to production, making it easier to move fast without breaking things. Get version control, API, & CLI included. - Data Operations: With Rivery, you get centralized logging & reporting, monitoring & alerts, and data quality as part of a robust data operations layer for your data pipelines. - Solution-Led Support: Consistently rated the best support by G2, receive engineering-led assistance from Rivery to facilitate all your data needs. - Data Security: Industry-leading security and enterprise-grade privacy standards are built into Rivery’s network, product, and policies. **Average Rating:** 4.7/5.0 **Total Reviews:** 120 **How Do G2 Users Rate Boomi Data Integration?** - **Has the product been a good partner in doing business?:** 9.6/10 (Category avg: 9.1/10) - **Automation:** 9.5/10 (Category avg: 9.0/10) - **Scalability:** 9.3/10 (Category avg: 8.7/10) - **Auditing:** 8.8/10 (Category avg: 8.1/10) **Who Is the Company Behind Boomi Data Integration?** - **Seller:** [Boomi](https://www.g2.com/sellers/boomi) - **Year Founded:** 2000 - **HQ Location:** Conshohocken, PA - **Twitter:** @boomi (101,014 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/boomi-inc/ (3,024 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 42% Mid-Market, 36% Small-Business #### What Are Boomi Data Integration's Pros and Cons? **Pros:** - Ease of Use (5 reviews) - Customer Support (4 reviews) - Data Management (4 reviews) - Automation (3 reviews) - Implementation Ease (3 reviews) **Cons:** - Data Limitations (1 reviews) - Information Deficiency (1 reviews) - Insufficient Information (1 reviews) - Lacking Features (1 reviews) - Limited Features (1 reviews) ### What Do G2 Reviewers Say About Boomi Data Integration? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Boomi Data Integration, making it friendly for both new and experienced users. - Users praise the **exceptional customer support** of Boomi Data Integration, making implementation and assistance seamless and effective. - Users value the **comprehensive data management** capabilities of Boomi Data Integration, streamlining workflows and enhancing analysis efficiency. - Users value the **automation capabilities** of Boomi Data Integration, enhancing efficiency in scheduling and managing data workflows. - Users appreciate the **implementation ease** of Boomi Data Integration, benefiting from intuitive onboarding and excellent customer support. **Cons:** - Users report encountering **data limitations** , such as missing documentation and unavailable fields, complicating their integration efforts. - Users face **information deficiency** with Boomi Data Integration, encountering missing documentation and unavailable report fields. - Users often face **insufficient information** when connecting to data sources, complicating their integration efforts. - Users frequently encounter **missing features** in Boomi Data Integration, leading to challenges with data source connectivity and reporting. - Users find the **limited features** of Boomi Data Integration hinder effective connections to various data sources. #### What Are Recent G2 Reviews of Boomi Data Integration? **"[Actual review of ELT Tool Rivery](https://www.g2.com/survey_responses/boomi-data-integration-review-10179408)"** **Rating:** 5.0/5.0 stars *— Amit K.* [Read full review](https://www.g2.com/survey_responses/boomi-data-integration-review-10179408) --- **"[Boomi Data Integration: Fast, Reliable Integrations at Scale](https://www.g2.com/survey_responses/boomi-data-integration-review-12546768)"** **Rating:** 5.0/5.0 stars *— Takkellapati S.* [Read full review](https://www.g2.com/survey_responses/boomi-data-integration-review-12546768) --- #### What Are G2 Users Discussing About Boomi Data Integration? - [What advice do you have for others considering Rivery for data integration and pipeline management?](https://www.g2.com/discussions/what-advice-do-you-have-for-others-considering-rivery-for-data-integration-and-pipeline-management) - [What is the use of Rivery?](https://www.g2.com/discussions/what-is-the-use-of-rivery) - 2 comments - [How much does Rivery cost?](https://www.g2.com/discussions/how-much-does-rivery-cost) - 1 comment - [What does Rivery do?](https://www.g2.com/discussions/what-does-rivery-do) - 1 comment ### 13. [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews) Azure Data Factory (ADF) is a fully managed, serverless data integration service designed to simplify the process of ingesting, preparing, and transforming data from diverse sources. It enables organizations to construct and orchestrate Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows in a code-free environment, facilitating seamless data movement and transformation across on-premises and cloud-based systems. Key Features and Functionality: - Extensive Connectivity: ADF offers over 90 built-in connectors, allowing integration with a wide array of data sources, including relational databases, NoSQL systems, SaaS applications, APIs, and cloud storage services. - Code-Free Data Transformation: Utilizing mapping data flows powered by Apache Spark™, ADF enables users to perform complex data transformations without writing code, streamlining the data preparation process. - SSIS Package Rehosting: Organizations can easily migrate and extend their existing SQL Server Integration Services (SSIS) packages to the cloud, achieving significant cost savings and enhanced scalability. - Scalable and Cost-Effective: As a serverless service, ADF automatically scales to meet data integration demands, offering a pay-as-you-go pricing model that eliminates the need for upfront infrastructure investments. - Comprehensive Monitoring and Management: ADF provides robust monitoring tools, allowing users to track pipeline performance, set up alerts, and ensure efficient operation of data workflows. Primary Value and User Solutions: Azure Data Factory addresses the complexities of modern data integration by providing a unified platform that connects disparate data sources, automates data workflows, and facilitates advanced data transformations. This empowers organizations to derive actionable insights from their data, enhance decision-making processes, and accelerate digital transformation initiatives. By offering a scalable, cost-effective, and code-free environment, ADF reduces the operational burden on IT teams and enables data engineers and business analysts to focus on delivering value through data-driven strategies. **Average Rating:** 4.6/5.0 **Total Reviews:** 95 **How Do G2 Users Rate Azure Data Factory?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.1/10) - **Automation:** 9.2/10 (Category avg: 9.0/10) - **Scalability:** 9.1/10 (Category avg: 8.7/10) - **Auditing:** 8.4/10 (Category avg: 8.1/10) **Who Is the Company Behind Azure Data Factory?** - **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft) - **Year Founded:** 1975 - **HQ Location:** Redmond, Washington - **Twitter:** @microsoft (13,091,739 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/microsoft/ (231,632 employees on LinkedIn®) - **Ownership:** MSFT **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 60% Enterprise, 30% Mid-Market #### What Are Azure Data Factory's Pros and Cons? **Pros:** - Data Integration (7 reviews) - Ease of Use (7 reviews) - Connectors (6 reviews) - Integrations (6 reviews) - Scalability (5 reviews) **Cons:** - Debugging Difficulty (5 reviews) - Difficult Debugging (4 reviews) - Expensive (4 reviews) - Feature Limitations (4 reviews) - Complexity (3 reviews) ### What Do G2 Reviewers Say About Azure Data Factory? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **seamless data integration** capabilities of Azure Data Factory, enhancing efficiency and simplifying complex workflows. - Users find Azure Data Factory's **ease of use** invaluable for integrating diverse data sources effortlessly and efficiently. - Users appreciate the **ease of connecting various data sources** with Azure Data Factory, simplifying complex data integration tasks. - Users appreciate the **seamless integration** capabilities of Azure Data Factory, simplifying data management across diverse sources. - Users value the **scalability** of Azure Data Factory, enabling effortless management of extensive data integration workflows. **Cons:** - Users find **debugging difficult** in Azure Data Factory, especially for complex pipelines with limited troubleshooting tools. - Users find **difficult debugging** in Azure Data Factory frustrating, especially with complex pipelines and limited troubleshooting tools. - Users find Azure Data Factory's **cost management challenging** , especially with high expenses for large data volumes. - Users find Azure Data Factory's **feature limitations** restrict effective logging, monitoring, and complex data transformations. - Users find Azure Data Factory's **complexity and limitations** overwhelming, especially in debugging and integrating with non-Azure services. #### What Are Recent G2 Reviews of Azure Data Factory? **"[Intuitive, Scalable Data Integration with Azure Data Factory](https://www.g2.com/survey_responses/azure-data-factory-review-12454264)"** **Rating:** 4.5/5.0 stars *— Alan R.* [Read full review](https://www.g2.com/survey_responses/azure-data-factory-review-12454264) --- **"[Low-Code Drag-and-Drop That Makes Development Easy for Developers and Business Users](https://www.g2.com/survey_responses/azure-data-factory-review-12746463)"** **Rating:** 4.5/5.0 stars *— Shyam s.* [Read full review](https://www.g2.com/survey_responses/azure-data-factory-review-12746463) --- #### What Are G2 Users Discussing About Azure Data Factory? - [Is Azure data Factory an ETL tool?](https://www.g2.com/discussions/is-azure-data-factory-an-etl-tool) - 2 comments - [What are the additional capabilities of data Factory?](https://www.g2.com/discussions/what-are-the-additional-capabilities-of-data-factory) - [Which 3 types of activities can you run in Microsoft Azure data Factory?](https://www.g2.com/discussions/which-3-types-of-activities-can-you-run-in-microsoft-azure-data-factory) - [What does Azure data/factory do?](https://www.g2.com/discussions/what-does-azure-data-factory-do) ### 14. [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews) IBM StreamSets is a robust streaming data integration tool for hybrid, multi-cloud environments that enables real-time decision making. It allows ingestion and in-flight transformation of structured, unstructured, and semi-structured data from streaming sources, and reliably delivers trusted data into diverse destinations. Flexible deployment options promote security, cost-effectiveness and performance. With several pre-built connectors, an intuitive no-code/low-code interface, and automatic adaptability to data drifts, StreamSets accelerates data pipeline operationalization. It integrates with IBM’s broader data integration capabilities, enabling reliable pipelines that unify multiple data integration patterns, underpinned by data observability capabilities for continuous data quality monitoring and remediation. That’s why the largest companies in the world trust StreamSets to power millions of data pipelines for modern analytics, data science, smart applications, and hybrid integration. **Average Rating:** 4.0/5.0 **Total Reviews:** 115 **How Do G2 Users Rate IBM StreamSets?** - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 9.1/10) - **Automation:** 7.7/10 (Category avg: 9.0/10) - **Scalability:** 7.6/10 (Category avg: 8.7/10) - **Auditing:** 7.2/10 (Category avg: 8.1/10) **Who Is the Company Behind IBM StreamSets?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 42% Enterprise, 33% Mid-Market #### What Are IBM StreamSets's Pros and Cons? **Pros:** - Ease of Use (30 reviews) - User Interface (16 reviews) - Data Management (15 reviews) - Data Pipelining (15 reviews) - Integrations (14 reviews) **Cons:** - Learning Curve (13 reviews) - Expensive (10 reviews) - Learning Difficulty (8 reviews) - Slow Performance (8 reviews) - Steep Learning Curve (8 reviews) ### What Do G2 Reviewers Say About IBM StreamSets? *AI-generated summary from verified user reviews* **Pros:** - Users value the **intuitive interface** of IBM StreamSets, making data pipeline creation and monitoring effortless and user-friendly. - Users appreciate the **user-friendly drag-and-drop interface** of IBM StreamSets, enhancing pipeline visualization and debugging efficiency. - Users appreciate the **effective data management** capabilities of IBM StreamSets for seamless pipeline creation and monitoring. - Users appreciate the **intuitive visual pipeline design** of IBM StreamSets, which simplifies data integration workflows for everyone. - Users value the **extensive integrations** of IBM StreamSets, enhancing data workflows across cloud and on-premise systems. **Cons:** - Users find the **steep learning curve** challenging, requiring deep technical knowledge to utilize advanced features effectively. - Users find the **product expensive** , especially for smaller teams, making it less competitive compared to alternatives. - Users find the **learning difficulty** to be challenging, especially with advanced features requiring significant time and effort. - Users experience **slow performance** with IBM StreamSets, especially when managing large datasets or complex pipelines. - Users find the **steep learning curve** challenging, requiring extensive technical knowledge for advanced features and configurations. #### What Are Recent G2 Reviews of IBM StreamSets? **"[Powerful Data Integration With IBM Stream sets.](https://www.g2.com/survey_responses/ibm-streamsets-review-11654909)"** **Rating:** 5.0/5.0 stars *— Abhishek D.* [Read full review](https://www.g2.com/survey_responses/ibm-streamsets-review-11654909) --- **"[Simplifies Real-Time Data Pipelines with Mixed Customization](https://www.g2.com/survey_responses/ibm-streamsets-review-12240946)"** **Rating:** 4.0/5.0 stars *— Sravya A.* [Read full review](https://www.g2.com/survey_responses/ibm-streamsets-review-12240946) --- #### What Are G2 Users Discussing About IBM StreamSets? - [What is StreamSets used for?](https://www.g2.com/discussions/what-is-streamsets-used-for) - [What is StreamSets data collector?](https://www.g2.com/discussions/what-is-streamsets-data-collector) - [What is StreamSets control hub?](https://www.g2.com/discussions/what-is-streamsets-control-hub) - [Are StreamSets free?](https://www.g2.com/discussions/are-streamsets-free) - [What is StreamSets tool?](https://www.g2.com/discussions/what-is-streamsets-tool) - 1 comment ### 15. [5X](https://www.g2.com/products/5x/reviews) 5X is an end-to-end data and AI platform. The platform organizes your data regardless of source or format. Whether you have a dedicated data team or not, our platform
transforms fragmented data into actionable insights and apps. The customer feedback we get most often is, "This is self-explanatory," and "It's super easy to use." And that is exactly what our goal was—to create a powerful, all-in-one platform that's incredibly easy to use.  The modern data stack has evolved. It's no longer about stitching together vendors. The next-generation modern data stack is an all-in-one platform that offers speed, simplicity, and decreased cost of ownership. That's exactly what we have created at 5X. Companies use 5X for multiple reasons: 1) Speed & productivity. All-in-one data platforms are incredibly efficient. We've seen companies build use cases on day 1.  Contact us to see if you qualify for a free 48 hour jumpstart! 🚀 2) Decrease your total cost of ownership by 30% compared to building your own platform. This doesn't account the people hours needed to support a platform build 🤯 3) Use our full stack data consultancy for support on data engineering & analytics 👨‍💻 5X was founded in 2020 with presence in the USA, Singapore, UK and India. Our global team is 70+ people strong and rapidly growing. We’ve recently raised our seed round from Flybridge Capital and backed by top founders from companies like Datadog, Preset, Astronomer, Mode, Rudderstack and other prominent angel investors. For more information, visit 5X.co We don't just talk about speed and simplicity; we back it up with proof. Speak to us about our 48-hour jumpstart where we can build an end-to-end use case for you in 48 hours for free. **Average Rating:** 4.9/5.0 **Total Reviews:** 81 **How Do G2 Users Rate 5X?** - **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.1/10) - **Automation:** 9.5/10 (Category avg: 9.0/10) - **Scalability:** 9.5/10 (Category avg: 8.7/10) - **Auditing:** 9.4/10 (Category avg: 8.1/10) **Who Is the Company Behind 5X?** - **Seller:** [5X](https://www.g2.com/sellers/5x) - **Year Founded:** 2020 - **HQ Location:** San Francisco - **Twitter:** @DataWith5x (49 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/datawith5x/ (111 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 56% Mid-Market, 40% Small-Business #### What Are 5X's Pros and Cons? **Pros:** - Ease of Use (28 reviews) - Customer Support (18 reviews) - Features (14 reviews) - Integrations (13 reviews) - Data Integration (10 reviews) **Cons:** - Steep Learning Curve (5 reviews) - Complex Setup (4 reviews) - Feature Limitations (4 reviews) - Learning Curve (4 reviews) - Difficult Setup (3 reviews) ### What Do G2 Reviewers Say About 5X? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of 5X, finding its integration and UI intuitive and highly effective for their needs. - Users commend the **exceptional customer support** from 5X, appreciating their responsiveness and dedication to user experience. - Users highlight the **seamless data integration** and **interactive UI** of 5X, enhancing overall functionality and usability. - Users value the **seamless integration capabilities** of 5X, enabling easy connection with existing tools and workflows. - Users highlight the **seamless data integration** provided by 5X, enhancing collaboration and operational efficiency for teams. **Cons:** - Users find the **steep learning curve** challenging initially, requiring training sessions and support for effective use. - Users find the **complex setup** of 5X delays deployment and requires significant time to learn and implement. - Users note the **feature limitations** of 5X, indicating a need for more developed and mature functionalities. - Users face a **significant learning curve** with 5X, especially for advanced features and complex workflows. - Users find the **difficult setup** challenging, as it requires significant time and learning for effective deployment. #### What Are Recent G2 Reviews of 5X? **"[A reliable and scalable data partner](https://www.g2.com/survey_responses/5x-review-11889175)"** **Rating:** 5.0/5.0 stars *— Varinderjit K.* [Read full review](https://www.g2.com/survey_responses/5x-review-11889175) --- **"[Exceptional Support and User-Friendly Platform Driving Our Data Transformation](https://www.g2.com/survey_responses/5x-review-11903408)"** **Rating:** 4.0/5.0 stars *— Shuming F.* [Read full review](https://www.g2.com/survey_responses/5x-review-11903408) --- ### 16. [dbt](https://www.g2.com/products/dbt/reviews) dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. **Average Rating:** 4.7/5.0 **Total Reviews:** 207 **How Do G2 Users Rate dbt?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10) - **Automation:** 9.4/10 (Category avg: 9.0/10) - **Scalability:** 9.2/10 (Category avg: 8.7/10) - **Auditing:** 8.3/10 (Category avg: 8.1/10) **Who Is the Company Behind dbt?** - **Seller:** [dbt Labs](https://www.g2.com/sellers/dbt-labs) - **Year Founded:** 2016 - **HQ Location:** Philadelphia, US - **Twitter:** @getdbt (14,792 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/dbtlabs/ (874 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Analytics Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 56% Mid-Market, 27% Small-Business #### What Are dbt's Pros and Cons? **Pros:** - Ease of Use (34 reviews) - Features (21 reviews) - Automation (17 reviews) - Transformation (16 reviews) - Data Quality (14 reviews) **Cons:** - Limited Functionality (13 reviews) - Dependency Issues (12 reviews) - Steep Learning Curve (10 reviews) - Error Handling (9 reviews) - Error Reporting (9 reviews) ### What Do G2 Reviewers Say About dbt? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of dbt, facilitating intuitive data transformations and collaboration among teams. - Users value dbt for its **robust structure and documentation** , enhancing SQL transformations and team collaboration effectively. - Users value the **automation** capabilities of dbt, enhancing collaboration and making SQL transformations efficient and maintainable. - Users find dbt to be a **powerful tool for data transformation** , simplifying processes and enhancing transparency in analytics workflows. - Users value the **high data quality** provided by dbt, ensuring integrity and transparency in analytics workflows. **Cons:** - Users find **limited functionality** in dbt, causing delays and complications, especially during debugging and project expansion. - Users face significant **dependency issues** with dbt, making troubleshooting model errors and debugging time-consuming and frustrating. - Users find the **steep learning curve** of dbt challenging, particularly with mastering Jinja, Git, and complex dependencies. - Users face difficulties with **error handling** , struggling with unclear messages and insufficient documentation for troubleshooting. - Users often find **error reporting unclear** , complicating troubleshooting and making it difficult to identify root causes. #### What Are Recent G2 Reviews of dbt? **"[dbt Streamlines Data Pipelines with Powerful Incremental and SCD2 Features](https://www.g2.com/survey_responses/dbt-review-12712114)"** **Rating:** 5.0/5.0 stars *— Hithesh P.* [Read full review](https://www.g2.com/survey_responses/dbt-review-12712114) --- **"[Simple SQL-Driven Materializations with Powerful Lineage](https://www.g2.com/survey_responses/dbt-review-12985641)"** **Rating:** 5.0/5.0 stars *— Anish G.* [Read full review](https://www.g2.com/survey_responses/dbt-review-12985641) --- #### What Are G2 Users Discussing About dbt? - [What is DBT data Modelling?](https://www.g2.com/discussions/what-is-dbt-data-modelling) - 2 comments - [What is DBT technology?](https://www.g2.com/discussions/what-is-dbt-technology) - 2 comments - [What is DBT database tool?](https://www.g2.com/discussions/what-is-dbt-database-tool) - 1 comment - [What is DBT tool used for?](https://www.g2.com/discussions/what-is-dbt-tool-used-for) - 2 comments ### 17. [Maia](https://www.g2.com/products/matillion-maia/reviews) Maia is an AI Data Automation platform powered by autonomous AI agents that build, maintain, and evolve data products, thus eliminating manual data work. Maia empowers CDAOs and enterprise data teams to deliver data products at machine scale while maintaining governance. Its integrated platform combines specialized agents in Maia Team, grounded in the organizational data intelligence of the Maia Context Engine and executed through the governed data tools of Maia Foundation. Organizations like EDF, St. James’ Place, and Nature’s Touch use Maia to automate data work at scale, modernize platforms, and accelerate AI roadmaps without expanding headcount. See Maia for yourself. **Average Rating:** 4.5/5.0 **Total Reviews:** 119 **How Do G2 Users Rate Maia?** - **Has the product been a good partner in doing business?:** 8.4/10 (Category avg: 9.1/10) - **Automation:** 9.1/10 (Category avg: 9.0/10) - **Scalability:** 8.6/10 (Category avg: 8.7/10) - **Auditing:** 7.8/10 (Category avg: 8.1/10) **Who Is the Company Behind Maia?** - **Seller:** [Matillion](https://www.g2.com/sellers/matillion) - **Company Website:** https://www.matillion.com - **Year Founded:** 2011 - **HQ Location:** Salford, GB - **Twitter:** @matillion (7,362 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2360297/ (459 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 47% Mid-Market, 31% Enterprise #### What Are Maia's Pros and Cons? **Pros:** - Ease of Use (10 reviews) - Automation (5 reviews) - Simple (5 reviews) - User Interface (5 reviews) - ETL Efficiency (4 reviews) **Cons:** - Feature Limitations (9 reviews) - Expensive (4 reviews) - Limitations (4 reviews) - Cloud Dependency (3 reviews) - API Issues (2 reviews) ### What Do G2 Reviewers Say About Maia? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of Maia, allowing even beginners to quickly understand and navigate the platform. - Users love the **seamless automation** capabilities of Matillion, enhancing ETL processes through user-friendly features and integrations. - Users find Matillion's **simple UI** highly effective for easy configuration and understanding, enhancing their overall experience. - Users appreciate the **intuitive and user-friendly interface** of Matillion, making ETL processes simpler and more accessible. - Users commend Maia's **ETL efficiency** , noting seamless integration and user-friendly design that simplifies complex workflows. **Cons:** - Users experience **feature limitations** with Jython interpreter issues and difficulties in creating reusable templates, impacting job performance. - Users find Maia to be **expensive** , especially as data volumes increase, impacting overall cost-effectiveness. - Users face **job performance issues** due to the Jython interpreter and single-thread workflow limitations in Maia. - Users find the **cloud dependency** of Maia restrictive, experiencing limitations and added costs for scaling their needs. - Users find **API limitations** frustrating, particularly regarding administrative access and insufficient options for data export and retrieval. #### What Are Recent G2 Reviews of Maia? **"[Maia Makes Onboarding Fast with an Intuitive UI and Low-Code Pipelines](https://www.g2.com/survey_responses/maia-review-12942268)"** **Rating:** 4.5/5.0 stars *— Anthony S.* [Read full review](https://www.g2.com/survey_responses/maia-review-12942268) --- **"[Maia Scaled 800+ Pipeline Migrations Without Added Overhead](https://www.g2.com/survey_responses/maia-review-12920298)"** **Rating:** 5.0/5.0 stars *— Keith G.* [Read full review](https://www.g2.com/survey_responses/maia-review-12920298) --- #### What Are G2 Users Discussing About Maia? - [What is Matillion ETL used for?](https://www.g2.com/discussions/what-is-matillion-etl-used-for) - 1 comment - [What is Matillion Data Loader used for?](https://www.g2.com/discussions/what-is-matillion-data-loader-used-for) - [What are ETL tools used for?](https://www.g2.com/discussions/what-are-etl-tools-used-for) - [Is Matillion open source?](https://www.g2.com/discussions/is-matillion-open-source) - [What is ETL in software?](https://www.g2.com/discussions/what-is-etl-in-software) ### 18. [Coupler.io](https://www.g2.com/products/coupler-io/reviews) Coupler.io is a no-code data integration platform that provides instant access to 400+ sources and a world of insights — all in one place. It allows you to collect data from various cloud sources, transform it, and load it into spreadsheets, BI tools, data warehouses, and AI agents. No complex setup or deep technical expertise required. Trusted by 1M+ users, including companies like Uber, Netflix, and Airbus, Coupler.io streamlines data processes for marketers, data analysts, business owners, sales teams, e-commerce businesses, and financial professionals. With 1800+ ready-made integrations, Coupler.io allows you to automatically collect data from Google Analytics, Facebook Ads, GoHighLevel, Shopify, QuickBooks, and many other apps. You can blend data from multiple sources into Google Sheets, Looker Studio, Power BI, BigQuery, Claude, ChatGPT, and other destinations. Coupler.io makes data transformation easy with data joining and appending functions, filtering, formulas, and data set templates. To quick-start with reporting, explore Coupler.io's in-app dashboards and free dashboard templates gallery for third-party tools. You can also build custom dashboards from scratch. AI Insights interprets dashboards in seconds, highlighting trends and anomalies and providing actionable recommendations. Coupler.io's AI integrations enable real-time analysis of large, blended data through natural language conversations in AI chats. These allow businesses to make data-driven decisions, scale operations, and improve reporting efficiency. Coupler.io is a SOC 2-certified, reliable platform that follows the highest data security and privacy standards to keep your data protected. Take full control of your data, identify what works, and scale it with Coupler.io for holistic data management and analysis! **Average Rating:** 4.8/5.0 **Total Reviews:** 102 **How Do G2 Users Rate Coupler.io?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10) - **Automation:** 9.7/10 (Category avg: 9.0/10) - **Scalability:** 8.9/10 (Category avg: 8.7/10) - **Auditing:** 8.3/10 (Category avg: 8.1/10) **Who Is the Company Behind Coupler.io?** - **Seller:** [Railsware](https://www.g2.com/sellers/railsware) - **Year Founded:** 2007 - **HQ Location:** Kraków - **Twitter:** @railsware (2,116 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/122084/ (180 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Non-Profit Organization Management, Marketing and Advertising - **Company Size:** 67% Small-Business, 28% Mid-Market #### What Are Coupler.io's Pros and Cons? **Pros:** - Ease of Use (19 reviews) - Time-Saving (19 reviews) - Automation (18 reviews) - Integrations (15 reviews) - Data Integration (14 reviews) **Cons:** - Difficult Setup (5 reviews) - Complex Setup (4 reviews) - Learning Curve (4 reviews) - Expensive (3 reviews) - Lack of Information (3 reviews) ### What Do G2 Reviewers Say About Coupler.io? *AI-generated summary from verified user reviews* **Pros:** - Users value the **intuitive interface** of Coupler.io, making data integration and automation accessible for everyone. - Users love the **time-saving capabilities** of Coupler.io, drastically reducing manual work and enhancing data workflow efficiency. - Users value the **automation** capabilities of Coupler.io, significantly reducing manual work and enhancing reporting efficiency. - Users value the **massive integration library** of Coupler.io, enabling quick connections to various platforms effortlessly. - Users praise Coupler.io for its **efficient data integration** capabilities, transforming complex data workflows into seamless reporting processes. **Cons:** - Users find the **difficult setup** process for complex data models and niche integrations to be quite tedious. - Users find the **setup process complex** , requiring trial and error, especially for advanced data models and integrations. - Users experience a **small learning curve** with Coupler.io, particularly when navigating data schemas and transformations initially. - Users find Coupler.io to be **expensive** , especially with multiple channels and limited licenses for smaller teams. - Users experience a **lack of information** regarding advanced features and detailed documentation, limiting their effectiveness with Coupler.io. #### What Are Recent G2 Reviews of Coupler.io? **"[Easy way to connect Power BI to Quickbooks](https://www.g2.com/survey_responses/coupler-io-review-12796693)"** **Rating:** 5.0/5.0 stars *— Yassine L.* [Read full review](https://www.g2.com/survey_responses/coupler-io-review-12796693) --- **"[Helpful tool for syncing data with Airtable](https://www.g2.com/survey_responses/coupler-io-review-9448658)"** **Rating:** 4.5/5.0 stars *— Hannah P.* [Read full review](https://www.g2.com/survey_responses/coupler-io-review-9448658) --- #### What Are G2 Users Discussing About Coupler.io? - [What is Coupler.io used for?](https://www.g2.com/discussions/what-is-coupler-io-used-for) ### 19. [AWS Glue](https://www.g2.com/products/aws-glue/reviews) AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application develop-ment. You can discover and connect to 70+ diverse data sources, manage your data in a centralized data catalog, and visually create, run, and monitor ETL pipelines to load data into your data lakes. You can im-mediately search and query catalogued data using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum. **Average Rating:** 4.3/5.0 **Total Reviews:** 194 **How Do G2 Users Rate AWS Glue?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10) - **Automation:** 8.8/10 (Category avg: 9.0/10) - **Scalability:** 8.9/10 (Category avg: 8.7/10) - **Auditing:** 8.7/10 (Category avg: 8.1/10) **Who Is the Company Behind AWS Glue?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,232,483 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 49% Enterprise, 29% Mid-Market #### What Are AWS Glue's Pros and Cons? **Pros:** - Ease of Use (6 reviews) - Data Integration (3 reviews) - ETL Solutions (3 reviews) - Features (3 reviews) - Simple (3 reviews) **Cons:** - Slow Performance (3 reviews) - Debugging Difficulty (2 reviews) - Difficult Debugging (2 reviews) - Performance Issues (2 reviews) - Time-Consuming (2 reviews) ### What Do G2 Reviewers Say About AWS Glue? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of AWS Glue, finding it straightforward for data preparation and analytics tasks. - Users appreciate the **seamless data integration** capabilities of AWS Glue, enabling efficient data movement and transformation. - Users appreciate the **fully managed ETL service** of AWS Glue, enjoying seamless integration and ease of use. - Users appreciate the **functionality and versatility** of AWS Glue, enabling easy data discovery and job execution. - Users value the **ease of implementation** in AWS Glue, enhancing data integration and error tracing for scripts. **Cons:** - Users experience **slow performance** with AWS Glue, particularly during startup and debugging, which can hinder productivity. - Users find **debugging difficult** in AWS Glue due to unclear error messages and a steep learning curve. - Users often face **difficult debugging** processes in AWS Glue, complicating the troubleshooting experience and prolonging job startups. - Users experience **performance issues** with AWS Glue, including slow start-up times and complex debugging processes. - Users find AWS Glue **time-consuming** due to slow startup times and complex debugging processes, especially for beginners. #### What Are Recent G2 Reviews of AWS Glue? **"[Serverless ETL Made Easy with AWS Glue](https://www.g2.com/survey_responses/aws-glue-review-12864874)"** **Rating:** 5.0/5.0 stars *— mani s.* [Read full review](https://www.g2.com/survey_responses/aws-glue-review-12864874) --- **"[AWS Glue Makes ETL Simple with Serverless Scalability and Deep AWS Integration](https://www.g2.com/survey_responses/aws-glue-review-12380790)"** **Rating:** 4.5/5.0 stars *— Pradip G.* [Read full review](https://www.g2.com/survey_responses/aws-glue-review-12380790) --- #### What Are G2 Users Discussing About AWS Glue? - [What is AWS Glue and how it works?](https://www.g2.com/discussions/what-is-aws-glue-and-how-it-works) - 1 comment - [What does AWS Glue do?](https://www.g2.com/discussions/what-does-aws-glue-do) - 2 comments - [What are the main components of AWS Glue?](https://www.g2.com/discussions/what-are-the-main-components-of-aws-glue) - 2 comments - [What are the features of glue?](https://www.g2.com/discussions/what-are-the-features-of-glue) - 1 comment ### 20. [Matia](https://www.g2.com/products/matia/reviews) Matia is a data operations platform that enables modern data teams to build, manage, and monitor end-to-end data pipelines in one place. Matia allows data teams to spend time managing their data, instead of their tools. Matia combines ingestion, reverse ETL, data cataloging, and observability into a single, unified interface. Rather than stitching together multiple tools for data movement, observability, and metadata tracking, teams use Matia to streamline their workflow, reduce vendor bloat, and improve data trust across the organization. Common use cases include syncing operational data into warehouse destinations, monitoring pipeline health with built-in alerts, documenting data assets automatically, and aligning data delivery with business-critical SLAs. Teams adopt Matia to simplify their stack, reduce engineering overhead, and create more transparent, reliable data infrastructure. **Average Rating:** 4.9/5.0 **Total Reviews:** 32 **How Do G2 Users Rate Matia?** - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.1/10) - **Automation:** 9.9/10 (Category avg: 9.0/10) - **Scalability:** 9.8/10 (Category avg: 8.7/10) - **Auditing:** 9.6/10 (Category avg: 8.1/10) **Who Is the Company Behind Matia?** - **Seller:** [Matia](https://www.g2.com/sellers/matia) - **Company Website:** https://www.matia.io - **Year Founded:** 2023 - **HQ Location:** Miami, US - **LinkedIn® Page:** http://linkedin.com/company/matia-data (54 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Financial Services, Computer Software - **Company Size:** 59% Mid-Market, 25% Small-Business #### What Are Matia's Pros and Cons? **Pros:** - Customer Support (20 reviews) - Ease of Use (15 reviews) - Features (14 reviews) - Implementation Ease (10 reviews) - Easy Integrations (9 reviews) **Cons:** - Limited Connectors (4 reviews) - Not User-Friendly (3 reviews) - Poor UI (3 reviews) - Limited Features (2 reviews) - Limited Integration (2 reviews) ### What Do G2 Reviewers Say About Matia? *AI-generated summary from verified user reviews* **Pros:** - Users commend Matia's **exceptional customer support** , highlighting quick assistance and dedicated service for mission-critical needs. - Users find Matia's interface to be **easy to use** , helping streamline pipeline creation with excellent support. - Users praise Matia for its **outstanding support** and **exceptional scalability** in handling large volumes of data effectively. - Users find **Matia's implementation easy** , appreciating the responsive support and streamlined DataOps features all in one platform. - Users value the **easy integrations** of Matia, appreciating its intuitive UI and seamless transition process for new setups. **Cons:** - Users note the **limited connectors** available in Matia, though the team is responsive to integration requests. - Users find Matia's **UI unintuitive** and slow, especially as their schemas grow and complexity increases. - Users find the **UI unintuitive and sluggish** , highlighting the need for improvements in user experience and speed. - Users note the **limited features** compared to major competitors, but commend the team's responsiveness to requests. - Users find the **limited integration options** with Matia somewhat slow and challenging for a seamless experience. #### What Are Recent G2 Reviews of Matia? **"[Excellent tooling backed by a highly supportive team](https://www.g2.com/survey_responses/matia-review-12338799)"** **Rating:** 5.0/5.0 stars *— Verified User in Security and Investigations* [Read full review](https://www.g2.com/survey_responses/matia-review-12338799) --- **"[Seamless Transition, Outstanding Value](https://www.g2.com/survey_responses/matia-review-12570399)"** **Rating:** 5.0/5.0 stars *— Jonah J.* [Read full review](https://www.g2.com/survey_responses/matia-review-12570399) --- ### 21. [Adverity](https://www.g2.com/products/adverity/reviews) Centralized Data Management for the Modern Marketer Adverity is the marketing intelligence platform that empowers agencies and enterprises to transform complex data into confident, AI-powered decisions. Through automated connectivity to 600+ data sources and destinations, unrivalled data transformation capabilities, powerful data governance, and built-in agentic and conversational AI for streamlined data access and insight activation, Adverity enables smarter, faster decision-making. Adverity is used by leading brands and agencies including Unilever, Bosch, IKEA, Barilla, Forbes, GroupM, Publicis, Dentsu, and more. **Average Rating:** 4.4/5.0 **Total Reviews:** 310 **How Do G2 Users Rate Adverity?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.1/10) - **Automation:** 9.1/10 (Category avg: 9.0/10) - **Scalability:** 8.3/10 (Category avg: 8.7/10) - **Auditing:** 7.9/10 (Category avg: 8.1/10) **Who Is the Company Behind Adverity?** - **Seller:** [Adverity GmbH](https://www.g2.com/sellers/adverity-gmbh) - **Company Website:** https://www.adverity.com - **Year Founded:** 2015 - **HQ Location:** Vienna, Austria - **Twitter:** @myadverity (1,757 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/5340622/ (312 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Data Engineer - **Top Industries:** Marketing and Advertising, Information Technology and Services - **Company Size:** 43% Mid-Market, 38% Small-Business #### What Are Adverity's Pros and Cons? **Pros:** - Ease of Use (16 reviews) - Integrations (11 reviews) - Data Management (10 reviews) - Easy Integrations (10 reviews) - User Interface (10 reviews) **Cons:** - Time-Consuming (7 reviews) - Complex Setup (4 reviews) - Data Management (4 reviews) - Difficult Learning (4 reviews) - Limited Customization (4 reviews) ### What Do G2 Reviewers Say About Adverity? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **clear and friendly interface** of Adverity, enhancing their ease of use for data management. - Users value the **extensive integrations** of Adverity, seamlessly connecting with all major marketing platforms and data sources. - Users value the **seamless data integration** capabilities of Adverity, ensuring efficient workflows and centralized data management. - Users value the **easy integrations** of Adverity, allowing seamless connections across numerous marketing platforms effortlessly. - Users love the **clear and intuitive user interface** of Adverity, making data management simple and efficient. **Cons:** - Users express concerns about the **time-consuming nature** of Adverity, especially when scaling and running multiple data pipelines. - Users find the **complex setup** of Adverity time-consuming and difficult, often requiring support for advanced features. - Users find the **data management complexities** overwhelming initially, requiring significant maintenance and setup to function effectively. - Users find the **difficult learning curve** of Adverity challenging, particularly regarding setup and advanced features. - Users find **limited customization** options frustrating, often needing to export data for tailored analysis and reporting. #### What Are Recent G2 Reviews of Adverity? **"[Adverity’s Flexible Dashboards and Powerful Multi-Source Analytics](https://www.g2.com/survey_responses/adverity-review-12834123)"** **Rating:** 4.5/5.0 stars *— Franziska K.* [Read full review](https://www.g2.com/survey_responses/adverity-review-12834123) --- **"[Adverity: Intuitive & Integrated](https://www.g2.com/survey_responses/adverity-review-12953180)"** **Rating:** 4.5/5.0 stars *— Verified User in Marketing and Advertising* [Read full review](https://www.g2.com/survey_responses/adverity-review-12953180) --- #### What Are G2 Users Discussing About Adverity? - [What is Adverity used for?](https://www.g2.com/discussions/what-is-adverity-used-for) - 1 comment ### 22. [Coefficient](https://www.g2.com/products/coefficient/reviews) Coefficient is a new way to work with your company data better, faster, and more accurately without ever leaving your spreadsheet, integrating with the tools you already use. Install the Coefficient Excel or Google Sheets extension and use it in a new or existing sheet in seconds. Once installed, Coefficient lives as a sidebar companion so your company data is only a couple of clicks away at any time. Any data source that you work with is available directly in your Coefficient sidebar – such as Salesforce, HubSpot, Snowflake, NetSuite, QuickBooks, MySQL, and Looker – with the ability to consolidate your data from multiple systems into one spreadsheet. Use Coefficient filters to easily customize your imports to only work with the data you need, keeping your spreadsheets performant. Quickly go back anytime to add more data in the same report. Never rebuild the same analysis twice by keeping your data up to date with scheduled updates. And, use Coefficient alerts to trigger Slack or email messages anytime your spreadsheet updates. Now, you can turn your spreadsheet into the most flexible, powerful monitoring system across all of your company data. Say “goodbye” to manual data workflows and “hello” to connected spreadsheets. **Average Rating:** 4.7/5.0 **Total Reviews:** 189 **How Do G2 Users Rate Coefficient?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 9.1/10) - **Automation:** 9.3/10 (Category avg: 9.0/10) - **Scalability:** 9.3/10 (Category avg: 8.7/10) - **Auditing:** 8.6/10 (Category avg: 8.1/10) **Who Is the Company Behind Coefficient?** - **Seller:** [Coefficient](https://www.g2.com/sellers/coefficient) - **Company Website:** https://coefficient.io/ - **Year Founded:** 2020 - **HQ Location:** Palo Alto, CA - **Twitter:** @coefficient_io (346 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/coefficientworks/ (71 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 47% Mid-Market, 35% Small-Business #### What Are Coefficient's Pros and Cons? **Pros:** - Ease of Use (72 reviews) - Automation (42 reviews) - Integrations (42 reviews) - Time-saving (36 reviews) - Easy Integrations (31 reviews) **Cons:** - Limited Features (18 reviews) - Feature Limitations (17 reviews) - Limitations (13 reviews) - Missing Features (12 reviews) - Integration Issues (11 reviews) ### What Do G2 Reviewers Say About Coefficient? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Coefficient, highlighting its seamless integration and effortless data handling. - Users appreciate the **seamless automation** in Coefficient, highlighting its simplicity and efficiency across multiple platforms. - Users appreciate the **seamless integrations** of Coefficient, highlighting its simplicity and efficiency in implementation. - Users enjoy the **time-saving features** of Coefficient, allowing quick data imports and effortless refreshing with a click. - Users value the **easy integrations** with databases and Salesforce, significantly enhancing their data management efficiency. **Cons:** - Users find the **limited features** of Coefficient inadequate, especially regarding filtering and basic functionalities. - Users note the **feature limitations** of Coefficient, particularly with bulk updates and filter options. - Users note a **limitation on data processing** with Coefficient, affecting usability and notification of missing data. - Users find the **missing features** , such as bulk updates and connectors, limit Coefficient's functionality and integration. - Users face **integration issues** with Coefficient, noting limited customizability and slow data connection to Sheets. #### What Are Recent G2 Reviews of Coefficient? **"[Effortless Scheduled Refreshes. Eliminates Manual Exports and Makes Revenue Data Actionable](https://www.g2.com/survey_responses/coefficient-review-12318636)"** **Rating:** 5.0/5.0 stars *— Jacob R.* [Read full review](https://www.g2.com/survey_responses/coefficient-review-12318636) --- **"[Effortless Salesforce to Sheets Integration](https://www.g2.com/survey_responses/coefficient-review-12701723)"** **Rating:** 5.0/5.0 stars *— Ellen Dericks C.* [Read full review](https://www.g2.com/survey_responses/coefficient-review-12701723) --- ### 23. [Weld](https://www.g2.com/products/weld-weld/reviews) Weld delivers an ultra-fast, secure, and reliable way to move data from all your tools, applications, and databases into cloud data warehouses, such as Snowflake, BigQuery, and Databricks. Deploy data pipelines in minutes with connectors that adapt to schema changes, detect duplicates, self-heal on failure, and run without maintenance, so your data team can focus on insights, not infrastructure. **Average Rating:** 4.8/5.0 **Total Reviews:** 104 **How Do G2 Users Rate Weld?** - **Has the product been a good partner in doing business?:** 9.7/10 (Category avg: 9.1/10) - **Automation:** 8.9/10 (Category avg: 9.0/10) - **Scalability:** 9.2/10 (Category avg: 8.7/10) - **Auditing:** 7.9/10 (Category avg: 8.1/10) **Who Is the Company Behind Weld?** - **Seller:** [Weld](https://www.g2.com/sellers/weld-733aad41-2e36-4f42-9349-7d847f41d873) - **Company Website:** https://weld.app/ - **Year Founded:** 2021 - **HQ Location:** Copenhagen, DK - **Twitter:** @WeldHQ (98 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/weldhq/ (91 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** CEO - **Top Industries:** Retail, Computer Software - **Company Size:** 59% Small-Business, 40% Mid-Market #### What Are Weld's Pros and Cons? **Pros:** - Customer Support (10 reviews) - Ease of Use (9 reviews) - Automation (8 reviews) - Features (7 reviews) - Implementation Ease (7 reviews) **Cons:** - Limited Connectors (5 reviews) - Feature Limitations (3 reviews) - Limited Integrations (3 reviews) - Complex Setup (2 reviews) - Connection Issues (2 reviews) ### What Do G2 Reviewers Say About Weld? *AI-generated summary from verified user reviews* **Pros:** - Users highlight the **exceptional customer support** of Weld, providing quick resolutions and enhancing overall user experience. - Users commend the **ease of use** of Weld, finding it simple to connect data sources and integrate seamlessly. - Users appreciate the **automation capabilities** of Weld, significantly streamlining data integration and analysis for non-technical users. - Users highlight the **excellent customer support** and ease of setup, making the experience seamless and efficient. - Users highlight the **implementation ease** of Weld, simplifying setup and integration for smooth BI operations. **Cons:** - Users find the **limited connectors** in Weld's basic plan somewhat restrictive, impacting their overall integration capabilities. - Users find the **limited native connectors** in Weld's basic plan somewhat restrictive for their integration needs. - Users find the **limited integrations** in Weld, particularly with connectors, restricting for their needs. - Users find the **complex setup** challenging, especially when tracking property changes and debugging intricate queries. - Users occasionally face **connection issues** that may require attention, though Weld generally performs reliably once configured. #### What Are Recent G2 Reviews of Weld? **"[Easy Connector Setup and Great Value](https://www.g2.com/survey_responses/weld-review-12601466)"** **Rating:** 4.5/5.0 stars *— Lucas T.* [Read full review](https://www.g2.com/survey_responses/weld-review-12601466) --- **"[Seamless ETL with Stellar Support](https://www.g2.com/survey_responses/weld-review-12858335)"** **Rating:** 5.0/5.0 stars *— Edward S.* [Read full review](https://www.g2.com/survey_responses/weld-review-12858335) --- ### 24. [Parabola](https://www.g2.com/products/parabola/reviews) Parabola is the AI agent platform for ops and finance teams. You describe your messy, recurring processes (the work that lives in macros, Python scripts, and tribal knowledge today) like reconciliations, carrier billing audits, accruals, inventory checks, and PO matching. Parabola builds the agents that run them on schedule, handle the unstructured inputs (PDFs, screenshots, multi-tab spreadsheets) a human analyst would handle, and show their work at every step. Unlike black-box agents, every decision is inspectable, governable, and audit-ready, so the agent becomes the SOP your team can review, hand off, and update without re-prompting from scratch. Every Parabola engagement includes access to a team of automation engineers, who take learnings from thousands of prior engagements to help design, scope, and deploy agents ready for production scale, not as a demo. Ops and finance teams at On Running, WHOOP, Flexport, Fabletics, Kendo Brands, KIND Bar, Spindrift, and Uber Freight use Parabola to operationalize AI for the high-stakes recurring work generic chatbots and autonomous agents can't safely run. **Average Rating:** 4.9/5.0 **Total Reviews:** 53 **How Do G2 Users Rate Parabola?** - **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.1/10) - **Automation:** 9.6/10 (Category avg: 9.0/10) - **Scalability:** 9.3/10 (Category avg: 8.7/10) - **Auditing:** 8.0/10 (Category avg: 8.1/10) **Who Is the Company Behind Parabola?** - **Seller:** [Parabola](https://www.g2.com/sellers/parabola) - **Year Founded:** 2017 - **HQ Location:** San Francisco, CA - **Twitter:** @parabolahq - **LinkedIn® Page:** https://www.linkedin.com/company/7590028/ (76 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Consumer Goods, Computer Software - **Company Size:** 47% Mid-Market, 45% Small-Business #### What Are Parabola's Pros and Cons? **Pros:** - Automation (18 reviews) - Ease of Use (15 reviews) - Intuitive (9 reviews) - Time-saving (9 reviews) - Time-Saving (9 reviews) **Cons:** - Limitations (5 reviews) - Learning Curve (3 reviews) - Time-Consumption (3 reviews) - Data Inaccuracy (2 reviews) - Limited Export Options (2 reviews) ### What Do G2 Reviewers Say About Parabola? *AI-generated summary from verified user reviews* **Pros:** - Users enjoy the **efficient automation** capabilities of Parabola, saving time and simplifying complex workflows without coding. - Users value the **ease of use** of Parabola, enabling seamless automation without needing extensive technical skills. - Users find Parabola's **intuitive interface** incredibly easy to navigate, enabling efficient automation without coding skills. - Users highlight the **time-saving benefits** of Parabola, enabling efficient automation of repetitive tasks within workflows. - Users love how Parabola provides **massive time savings** , transforming workflows and automating tasks efficiently across teams. **Cons:** - Users find that the **requirement for unique steps in data manipulation** makes building flows cumbersome and lengthy. - Users face a **learning curve** with Parabola, which can complicate initial use and extend onboarding time. - Users find **time-consumption** challenging due to the necessity of unique steps for data manipulation, impacting workflow efficiency. - Users face issues with **data inaccuracy** in Parabola, requiring double-checking and caution with automated reports. - Users express frustration over **limited export options** , particularly with handling large datasets and inefficient data rewriting. #### What Are Recent G2 Reviews of Parabola? **"[Parabola Makes Automation Easy and Independently Driven](https://www.g2.com/survey_responses/parabola-review-12880670)"** **Rating:** 5.0/5.0 stars *— Krystal C.* [Read full review](https://www.g2.com/survey_responses/parabola-review-12880670) --- **"[Parabola Saves Hours with Accurate Automation and Responsive Support](https://www.g2.com/survey_responses/parabola-review-12893265)"** **Rating:** 4.5/5.0 stars *— Michelle I.* [Read full review](https://www.g2.com/survey_responses/parabola-review-12893265) --- #### What Are G2 Users Discussing About Parabola? - [What is Parabola used for?](https://www.g2.com/discussions/what-is-parabola-used-for) ### 25. [KNIME](https://www.g2.com/products/knime-analytics-platform/reviews) KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice. **Average Rating:** 4.5/5.0 **Total Reviews:** 89 **How Do G2 Users Rate KNIME?** - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 9.1/10) - **Automation:** 10.0/10 (Category avg: 9.0/10) - **Scalability:** 10.0/10 (Category avg: 8.7/10) - **Auditing:** 10.0/10 (Category avg: 8.1/10) **Who Is the Company Behind KNIME?** - **Seller:** [KNIME](https://www.g2.com/sellers/knime) - **Company Website:** https://knime.com - **Year Founded:** 2008 - **HQ Location:** Zurich, Switzerland - **Twitter:** @knime (7,998 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/692207?trk=tyah&trkInfo=clickedVertical%3Acompany%2CclickedEntityId%3A692207%2Cidx%3A2-1-4%2CtarId%3A1454002156993%2Ctas%3Aknime (241 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Higher Education - **Company Size:** 43% Enterprise, 34% Mid-Market #### What Are KNIME's Pros and Cons? **Pros:** - Ease of Use (7 reviews) - Coding Ease (4 reviews) - Ease of Learning (4 reviews) - Learning (4 reviews) - Data Visualization (3 reviews) **Cons:** - Learning Difficulty (3 reviews) - Memory Usage (3 reviews) - Storage Limitations (3 reviews) - Data Management Issues (2 reviews) - Insufficient Learning Resources (2 reviews) ### What Do G2 Reviewers Say About KNIME? *AI-generated summary from verified user reviews* **Pros:** - Users find KNIME's **ease of use** remarkable, allowing non-technical individuals to create workflows effortlessly. - Users find KNIME's **coding ease** exceptional, allowing non-technical users to build workflows effortlessly. - Users find KNIME **easy to learn** , enabling quick delivery of workflows without needing extensive technical knowledge. - Users praise KNIME for its **easy learning curve** , enabling both beginners and experts to create powerful data solutions. - Users praise the **ease of data visualization** in KNIME, making it accessible for both beginners and experienced analysts. **Cons:** - Users face a **challenging learning curve** with KNIME, especially if they lack data science or visual programming experience. - Users experience **high memory consumption** issues with KNIME, causing slow performance and challenges in handling large files. - Users experience **storage limitations** due to high memory consumption, affecting performance with large files. - Users find **data management issues** significant, citing difficulties with file handling and reading from various databases. - Users find **insufficient learning resources** for KNIME, which hinders their ability to fully utilize the software. #### What Are Recent G2 Reviews of KNIME? **"[KNIME’s Free No-Code Drag-and-Drop Analytics, from Descriptive to Agentic AI](https://www.g2.com/survey_responses/knime-review-12992618)"** **Rating:** 5.0/5.0 stars *— Guylaine B.* [Read full review](https://www.g2.com/survey_responses/knime-review-12992618) --- **"[KNIME’s Visual Workflows - One of the best tool for Auditing, Accounting & Finance Professionals](https://www.g2.com/survey_responses/knime-review-12976842)"** **Rating:** 5.0/5.0 stars *— Charm M.* [Read full review](https://www.g2.com/survey_responses/knime-review-12976842) --- #### What Are G2 Users Discussing About KNIME? - [What is KNIME Analytics Platform used for?](https://www.g2.com/discussions/what-is-knime-analytics-platform-used-for) - [Is Knime easy to use?](https://www.g2.com/discussions/is-knime-easy-to-use) - 1 comment - [How do I use Knime Analytics?](https://www.g2.com/discussions/how-do-i-use-knime-analytics) - [Is Knime any good?](https://www.g2.com/discussions/is-knime-any-good) - [What is Knime analytics platform?](https://www.g2.com/discussions/what-is-knime-analytics-platform) ## What Is ETL Tools? [Cloud Data Integration Software](https://www.g2.com/categories/cloud-data-integration) ## What Software Categories Are Similar to ETL Tools? - [On-Premise Data Integration Software](https://www.g2.com/categories/on-premise-data-integration) - [iPaaS Software](https://www.g2.com/categories/ipaas) - [Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms) - [Data Extraction Tools](https://www.g2.com/categories/data-extraction-tools) - [Data Replication Software](https://www.g2.com/categories/data-replication) - [DataOps Platforms](https://www.g2.com/categories/dataops-platforms) - [Reverse ETL Software](https://www.g2.com/categories/reverse-etl) --- ## How Do You Choose the Right ETL Tools? ### What You Should Know About ETL Tools ### ETL software buying insights at a glance Organizations today manage data across multiple applications, databases, and cloud environments. [ETL tools](https://www.g2.com/categories/etl-tools) help teams extract, transform, and load that data into centralized systems where it can be analyzed and used for reporting or operational decision-making. As companies adopt [cloud data warehouses](https://www.g2.com/categories/data-warehouse) and modern analytics stacks, these solutions play an important role in keeping data pipelines reliable and consistent.  The best ETL tools help organizations reduce manual scripting, maintain consistent data pipelines, and support large volumes of data across multiple integrations. As data environments grow more complex, ETL providers increasingly focus on simplifying integrations and enabling faster access to analytics-ready data. Common use cases focus on simplifying how data moves and gets prepared across systems. Teams use these tools to automate pipelines between SaaS apps, databases, and warehouses, consolidate data for unified reporting, and transform raw inputs into analytics-ready datasets for [BI tools](https://www.g2.com/categories/business-intelligence). They also help maintain consistent, reliable data flows across distributed environments, supporting cloud data warehouses and modern analytics platforms. Pricing varies across the category depending on the number of integrations, pipeline volume, and transformation complexity. Many vendors use usage-based pricing models tied to data volume or connectors. Entry-level plans often support smaller teams or limited pipelines, while enterprise deployments add advanced monitoring, governance, and scalability capabilities. ### Top 5 FAQs from software buyers - How do ETL tools support modern data stacks and cloud-based data architectures? - How well do ETL platforms integrate with cloud data warehouses like BigQuery, Snowflake, or Redshift? - Which ETL tools simplify pipeline management and reduce maintenance overhead for data teams? - What level of scalability and performance do ETL solutions provide for large-scale data pipelines? - Which ETL providers offer the broadest integration support across SaaS applications, databases, and APIs? G2’s top-rated ETL tools, based on verified reviews, include [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews), [Databricks](https://www.g2.com/products/databricks/reviews), [Domo](https://www.g2.com/products/domo/reviews), [Workato](https://www.g2.com/products/workato/reviews), and [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews). ### What are the top-reviewed ETL Tools on G2? [**Google Cloud BigQuery**](https://www.g2.com/products/google-cloud-bigquery/reviews) - Number of Reviews: 324 - Satisfaction: 98 - Market Score: 99 - G2 Score: 98 [**Databricks**](https://www.g2.com/products/databricks/reviews) - Number of Reviews: 279 - Satisfaction: 100 - Market Score: 81 - G2 Score: 90 [**Domo**](https://www.g2.com/products/domo/reviews) - Number of Reviews: 380 - Satisfaction: 88 - Market Score: 73 - G2 Score: 80 [**Workato**](https://www.g2.com/products/workato/reviews) - Number of Reviews: 224 - Satisfaction: 94 - Market Score: 62 - G2 Score: 78 [**SnapLogic Intelligent Integration Platform (IIP)**](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) - Number of Reviews: 172 - Satisfaction: 94 - Market Score: 60 - G2 Score: 77 **Satisfaction** reflects user-reported ratings, including ease of use, support, and feature fit. ([Source 2](https://www.g2.com/reports)) **Market Presence** scores combine review and external signals that indicate market momentum and footprint. ([Source 2](https://www.g2.com/reports)) **G2 Score** is a weighted composite of Satisfaction and Market Presence. ([Source 2](https://www.g2.com/reports)) Learn how G2 scores products. ([Source 1](https://documentation.g2.com/docs/research-scoring-methodologies?_gl=1*5vlk6s*_gcl_au*MTAwMzU5MzUxLjE3NjM0MTg0NzYuNjY0NTIxMTY0LjE3NjQ2MTc0NzcuMTc2NDYxNzQ3Nw..*_ga*NzY1MDU0NjE3LjE3NjM0NzQ3ODM.*_ga_MFZ5NDXZ5F*czE3NjYwODk1MTMkbzY3JGcxJHQxNzY2MDkyMjQyJGo1NyRsMCRoMA..)) ### What I Often See in ETL Tools #### Feedback Pros: What Users Consistently Appreciate • **Visual pipeline builders simplify complex multi-source data integrations** _“I love how the SnapLogic Intelligent Integration Platform (IIP) makes building integrations so easy with its AI-powered and low-code interface, which significantly streamlines design and maintenance for both technical and non-technical users. This platform guides the pipeline design and reduces the manual effort, aligning with its AI-driven workflow approach, and it has been instrumental in helping me automate workflows, improve data flow efficiency, and reduce the integration effort significantly. The initial setup was very easy because it's a cloud-based, self-service platform that minimizes installation effort and helps teams get started quickly. I highly recommend SnapLogic IIP for organizations looking to modernize and accelerate their integration strategy, and I would rate it a 9 for its ease of use.”_ - [Sanket N.](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews/snaplogic-intelligent-integration-platform-iip-review-12380685), SnapLogic Intelligent Integration Platform (IIP) review • **Extensive connectors enable fast integration across SaaS and databases** _“We use this every day as a vital part of an integration between our website and database. Easy to use with a number of different integrations available at your fingertips. Assistance was always an email away.”_ - [Nick E.](https://www.g2.com/products/skyvia/reviews/skyvia-review-12443772), Skyvia review • **Automation capabilities reduce manual pipeline maintenance and data preparation** _“Workato is an excellent tool for automating tasks and improving processes. What I find truly impressive is that we no longer have to rely on our ERP vendor for new features or automations; instead, we can handle everything ourselves using Workato. Personally, I have implemented numerous enhancements that have greatly benefited the Finance team, resulting in an estimated annual savings of around 1,000 hours. Also tool is so easy to use that you do not need to have any technical knowledge.”_ - [Manvitha K.](https://www.g2.com/products/workato/reviews/workato-review-12106615), Workato review #### Cons: Where Many Platforms Fall Short • **Advanced transformations require deeper technical knowledge and configuration** _“Some advanced use cases require a deeper technical understanding, especially when building custom flows, handling edge cases, or working with complex APIs. The UI can feel overwhelming for new users, and debugging large integrations could be improved with more developer-style tooling. Pricing can also be a consideration for smaller organizations compared to lightweight automation tools.”_ - [Nuri Vladimir E.](https://www.g2.com/products/celigo/reviews/celigo-review-12356472), Celigo review • **Limited debugging visibility when pipelines fail during complex workloads** _“Debugging and troubleshooting pipelines can sometimes be difficult. Error messages are not always very detailed, which can slow down the process of identifying issues. The UI is helpful, but complex pipelines can become harder to manage and visualize as they grow. Additionally, monitoring and cost tracking for large workloads requires careful attention, as pipeline executions and data movement activities can accumulate costs quickly.”_ - [Alan R.](https://www.g2.com/products/azure-data-factory/reviews/azure-data-factory-review-12454264), Azure Data Factory • **Scaling integrations or data volume increases operational management complexity** _“The pricing model can become expensive for large-scale queries without proper optimization and cost monitoring. The learning curve for advanced features and query optimization techniques requires time investment. Limited support for certain data types and occasional complexity in debugging nested queries could be improved for a better developer experience.”_ - [Alok K.](https://www.g2.com/products/google-cloud-bigquery/reviews/google-cloud-bigquery-review-12237841), Google Cloud BigQuery review ### My Expert Takeaway on ETL Tools in 2026 Looking across the review data, ETL solutions receive consistently strong sentiment, with an average rating of **4.61/5 stars and a 9.22/10 likelihood to recommend**. That tells me most teams see clear value once their pipelines are operational. ETL tools have quietly become core infrastructure for modern data environments, especially as organizations connect more SaaS applications, warehouses, and analytics systems. What I notice most in the reviews is that teams rarely evaluate ETL platforms only on integrations. Instead, reliability and automation come up repeatedly. Users want pipelines that run consistently without constant monitoring or manual fixes. When pipelines break or debugging becomes difficult, it quickly impacts reporting workflows and downstream analytics. Another pattern I see is that successful teams treat ETL software as shared infrastructure rather than an isolated engineering tool. Data engineers may design pipelines, but analysts and operations teams often rely on them daily. Platforms that simplify pipeline visibility, monitoring, and maintenance tend to make collaboration easier across teams. Industry usage patterns also suggest that organizations with growing data environments benefit the most from mature ETL workflows. For buyers evaluating the best ETL tools, the biggest differentiator often comes down to how well a platform keeps pipelines stable and manageable as data complexity grows. ### ETL Tools FAQs #### What are the best free ETL tools for developers? Many platforms offer open-source components, limited free tiers, or trial versions that developers use to build and test pipelines. Common options include: - [dbt](https://www.g2.com/products/dbt/reviews) **:** An open-source framework used by data teams to transform and model data directly inside data warehouses. - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Offers a limited free usage tier that allows developers to run queries and build data pipelines at small scale. - [AWS Glue](https://www.g2.com/products/aws-glue/reviews): A serverless data integration service commonly used for large-scale pipelines, typically accessed through free trial credits or limited testing environments. Developers often use these tools to prototype data pipelines before scaling to production workloads. #### What are the best no-code or low-code ETL tools? No-code and low-code ETL tools simplify pipeline creation through visual workflows and prebuilt integrations. Examples include: - [Workato](https://www.g2.com/products/workato/reviews): Known for its automation platform and extensive connector ecosystem that simplifies integration workflows. - [SnapLogic](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews): Uses a visual interface and prebuilt connectors to help teams design data pipelines without heavy coding. - [Alteryx](https://www.g2.com/products/alteryx/reviews): Offers a drag-and-drop workflow builder designed for analysts working with data preparation and transformation. These platforms allow data teams to manage pipelines without relying heavily on engineering resources. #### Which ETL services offer strong security features? Organizations handling sensitive data often prioritize ETL tools that offer strong governance, access controls, and compliance capabilities. Platforms commonly used in secure environments include: - [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews): Integrates with Microsoft’s identity and security framework for controlled data pipelines. - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Supports secure data processing with built-in encryption and governance capabilities. - [AWS Glue](https://www.g2.com/products/aws-glue/reviews): Provides role-based access controls and integration with AWS security services. These platforms help organizations maintain secure data movement across complex environments. #### What’s the leading ETL app for big data analysis? For large-scale analytics workloads, organizations often use ETL tools that integrate directly with modern data platforms. Common choices include: - [Databricks](https://www.g2.com/products/databricks/reviews): Designed for large-scale data engineering, analytics, and machine learning pipelines. - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Enables large-scale data processing and analytics within a cloud data warehouse environment. - [Fivetran](https://www.g2.com/products/fivetran/reviews): Automates high-volume data ingestion into cloud warehouses for analytics and reporting. These platforms support large datasets and complex transformation workflows. #### What are the different types of ETL tools? ETL tools generally fall into four categories: - **Open-source ETL tools** : Flexible frameworks for custom pipeline development. - **Cloud-based ETL platforms** : Managed services that automate data pipelines. - **No-code or low-code ETL tools** : Visual workflow tools for non-engineering teams. - **Enterprise ETL solutions** : Platforms built for governance, monitoring, and large-scale data environments. Each category supports different technical needs and levels of pipeline complexity. #### Sources - [G2 Scoring Methodologies](https://documentation.g2.com/docs/research-scoring-methodologies?_gl=1*5ky9es*_gcl_au*MTY2NDg2MDY3Ny4xNzU1MDQxMDU4*_ga*MTMwMTMzNzE1MS4xNzQ5MjMyMzg1*_ga_MFZ5NDXZ5F*czE3NTUwOTkzMjgkbzQkZzEkdDE3NTUwOTk3NzYkajU3JGwwJGgw) - [G2 Winter 2026 Reports](https://company.g2.com/news/g2-winter-2026-reports) Researched By: [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi) Last updated on March 16, 2026