# Best ETL Tools *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* 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 (1,217 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 | "[Celigo, a greta integrator with a University Lab inside it.](https://www.g2.com/survey_responses/celigo-review-10532295)" | | 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 (783 reviews) | Drag-and-drop data prep and reporting automation | "[Easy, Time-Saving Data Automation with Alteryx’s Drag-and-Drop Workflows](https://www.g2.com/survey_responses/alteryx-review-12594796)" | | 5 | [IBM watsonx.data](https://www.g2.com/products/ibm-watsonx-data/reviews) | 4.4/5.0 (159 reviews) | Lakehouse querying across object storage | "[Unified Data Management with Learning Curve](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742)" | | 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 (778 reviews) | Managed connector-based data ingestion | "[Simple Setup, Reliable Syncing, and Powerful Pre-Built Connectors](https://www.g2.com/survey_responses/fivetran-review-12945842)" | | 8 | [Workato](https://www.g2.com/products/workato/reviews) | 4.7/5.0 (745 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)" | | 9 | [Domo](https://www.g2.com/products/domo/reviews) | 4.3/5.0 (987 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)" | | 10 | [Skyvia](https://www.g2.com/products/skyvia/reviews) | 4.8/5.0 (319 reviews) | No-code CRM sync, backup, and scheduled ETL | "[Easy, No-Code Data Sync Setup with Straightforward Pricing](https://www.g2.com/survey_responses/skyvia-review-12828558)" | --- ## 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:** 248 ### Category Stats (Jun 2026) - **Average Rating**: 4.55/5 (↑0.01 vs May 2026) The average rating of products in this category, based on all submitted ratings - **New Reviews This Quarter**: 446 - **Buyer Segments**: Mid-Market 44% │ Small-Business 28% │ Enterprise 28% Represents the distribution of reviewers across all products in this category. - **Top Trending Product**: Maia (+0.84%) - Among all products in this category, Maia recorded the largest rating increase compared to last month *Last updated: June 09, 2026* ## How Does G2 Rank ETL Tools Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 18,800+ Authentic Reviews - 248+ 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** ### CData Sync Unlike volume-based tools with unpredictable pricing, CData Sync offers a single platform for ETL and reverse ETL, with full deployment flexibility and fixed, scalable pricing—so your costs don’t balloon as your data grows. Connect to 250+ enterprise data sources, including: • Salesforce, Microsoft Dynamics, and SAP • SharePoint, NetSuite, Workday, and QuickBooks • ServiceNow, Xero, Sage Intacct, HubSpot, Marketo, Oracle • …and many more Replicate that data into your preferred destinations, such as: • Snowflake, Databricks, SQL Server, Redshift, OneLake, and others Deploy it your way—on-premises, in your own cloud, or in a private-cloud SaaS model. Getting started is simple: 1. Log in 2. Select your source tables 3.Set your sync interval CData Sync handles the rest, using efficient incremental updates that minimize load on your operational systems. The platform includes: • Point-and-click ETL/ELT/reverse ETL • Change Data Capture (CDC) with no elevated database permissions • Complete data control and custom SQL transformations • dbt integration CData Sync centralizes your automated data flows, giving you full control, faster delivery, and the freedom to scale without hidden fees. Download a 30-day free trial of CData Sync or learn more at: www.cdata.com/sync [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=paid_promo&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1181&secure%5Bmedium%5D=sponsored&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=124922&secure%5Bresource_id%5D=1181&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fetl-tools%3Fpage%3D5&secure%5Btoken%5D=dbb35600fd5b33fcd49113c8e9e7d018b823a3fbe4f3e9b29eb289ab8ecae97b&secure%5Burl%5D=https%3A%2F%2Fwww.cdata.com%2Fsync%2F&secure%5Burl_type%5D=paid_promos) --- ## What Are the Top-Rated ETL Tools Products in 2026? ### 1. [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:** 1,217 **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:** 9.0/10 (Category avg: 9.0/10) - **Scalability:** 9.1/10 (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 (91,542 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) ### 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 (1,419 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) ### 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 (31,901,456 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:** - Speed (143 reviews) - Ease of Use (129 reviews) - Integrations (110 reviews) - Fast Querying (105 reviews) - Query Efficiency (100 reviews) **Cons:** - Expensive (127 reviews) - Query Issues (65 reviews) - Learning Curve (54 reviews) - Cost Management (52 reviews) - Cost Issues (51 reviews) ### 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:** 783 **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:** 9.6/10 (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 (26,153 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:** 64% 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) ### 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 (74,679 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) ### 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) ### 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:** 778 **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 (5,761 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) ### 8. [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:** 745 **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 (173 reviews) - Integrations (171 reviews) - Features (156 reviews) - Automation (149 reviews) **Cons:** - Complexity (70 reviews) - Learning Curve (58 reviews) - Data Limitations (55 reviews) - Missing Features (55 reviews) - Steep Learning Curve (48 reviews) ### 9. [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:** 987 **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 (63,526 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 (248 reviews) - Data Visualization (116 reviews) - Intuitive (95 reviews) - Easy Integrations (93 reviews) - Integrations (88 reviews) **Cons:** - Learning Curve (66 reviews) - Missing Features (59 reviews) - Data Management Issues (55 reviews) - Expensive (45 reviews) - Complexity (43 reviews) ### 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:** 319 **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 (1,738 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, Computer Software - **Company Size:** 52% Small-Business, 42% Mid-Market #### What Are Skyvia's Pros and Cons? **Pros:** - Ease of Use (50 reviews) - Easy Integrations (34 reviews) - Easy Setup (33 reviews) - Setup Ease (31 reviews) - Data Management (27 reviews) **Cons:** - Information Deficiency (8 reviews) - Difficult Setup (7 reviews) - Feature Limitations (7 reviews) - Learning Curve (7 reviews) - Poor Documentation (7 reviews) ### 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 (85 reviews) - Easy Integrations (70 reviews) - Integrations (54 reviews) - User Interface (50 reviews) - Automation (43 reviews) **Cons:** - Performance Issues (31 reviews) - Poor Performance (25 reviews) - Technical Difficulties (25 reviews) - Complexity (22 reviews) - Error Reporting (22 reviews) ### 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 (101,032 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) ### 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 (13,091,954 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) ### 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 (74,679 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) ### 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) ### 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:** 206 **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 (14,758 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:** 57% Mid-Market, 27% Small-Business #### What Are dbt's Pros and Cons? **Pros:** - Ease of Use (38 reviews) - Features (22 reviews) - Automation (19 reviews) - Transformation (17 reviews) - Integrations (15 reviews) **Cons:** - Limited Functionality (14 reviews) - Dependency Issues (12 reviews) - Steep Learning Curve (10 reviews) - Error Handling (9 reviews) - Error Reporting (9 reviews) ### 17. [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 (20 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) ### 18. [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:** 118 **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 (7,365 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:** Information Technology and Services, Computer Software - **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) ### 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 (2,231,239 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) ### 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) ### 21. [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:** 188 **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 (345 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, 36% 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) ### 22. [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:** - Ease of Use (16 reviews) - Customer Support (13 reviews) - Features (12 reviews) - Automation (11 reviews) - Data Integration (9 reviews) **Cons:** - Limited Connectors (8 reviews) - Feature Limitations (6 reviews) - Missing Features (5 reviews) - Limited Integrations (4 reviews) - Connectivity Issues (3 reviews) ### 23. [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) ### 24. [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:** 305 **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:** 9.0/10 (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 (1,756 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) ### 25. [Singular](https://www.g2.com/products/singular/reviews) Singular is the only end-to-end marketing attribution and analytics platform that uncovers true ROI across all marketing channels. We transform complex marketing data into actionable insights by unifying campaign data from thousands of channels with cross-device attribution data. Leading brands like LinkedIn, Nike, WB Games, and Rovio rely on Singular to maximize every marketing dollar, eliminate wasted spend, and drive higher user retention. With superior ROI reporting, advanced fraud prevention, user engagement capabilities, and unmatched data accessibility, marketers can finally drive faster growth with smarter insights. **Average Rating:** 4.5/5.0 **Total Reviews:** 501 **How Do G2 Users Rate Singular?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.1/10) - **Automation:** 8.9/10 (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 Singular?** - **Seller:** [Singular](https://www.g2.com/sellers/singular) - **Company Website:** https://www.singular.net - **Year Founded:** 2014 - **HQ Location:** Palo Alto, California - **Twitter:** @TweetSingular (1,316 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3739623/ (364 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** User Acquisition Manager, Marketing Manager - **Top Industries:** Computer Games, Financial Services - **Company Size:** 52% Mid-Market, 26% Small-Business #### What Are Singular's Pros and Cons? **Pros:** - Customer Support (80 reviews) - Ease of Use (64 reviews) - Helpful (47 reviews) - Features (46 reviews) - Reporting (36 reviews) **Cons:** - Poor Interface Design (18 reviews) - Poor UI (18 reviews) - Limitations (16 reviews) - Data Limitations (15 reviews) - Limited Attribution Capabilities (15 reviews) ## 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