# Best Enterprise ETL Tools

## How Many ETL Tools Products Does G2 Track?

**Total Products under this Category:** 254

### Category Stats (Jul 2026)

- **Average Rating:** 4.54/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Adeptia (+0.97%) - Among all products in this category, Adeptia recorded the largest rating increase compared to last month

_Last updated: July 31, 2026_

## How Does G2 Rank ETL Tools Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 19,300+ Authentic Reviews
- 254+ 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.

## G2 Grid® for ETL Tools
 ![G2 Grid® for ETL Tools plotting products by satisfaction and market presence](https://www.g2.com/categories/etl-tools/grids.png?focus%5B%5D=10470&focus%5B%5D=989&focus%5B%5D=6073&focus%5B%5D=69889&focus%5B%5D=52204&focus%5B%5D=40849&focus%5B%5D=604&focus%5B%5D=1308796)

Highlighted products: Databricks, Alteryx, Google Cloud BigQuery, IBM StreamSets, Azure Data Factory, AWS Glue, Domo, and IBM watsonx.data.

Underlying data: [Grid® JSON](https://www.g2.com/categories/etl-tools/grids.json?focus%5B%5D=databricks&focus%5B%5D=alteryx&focus%5B%5D=google-cloud-bigquery&focus%5B%5D=ibm-streamsets&focus%5B%5D=azure-data-factory&focus%5B%5D=aws-glue&focus%5B%5D=domo&focus%5B%5D=ibm-watsonx-data&segment=enterprise)

**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=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=1181&secure%5Bchosen_at%5D=2026-07-31T15%3A46%3A05Z&secure%5Bdisplayable_resource_id%5D=1181&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1181&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%2Fenterprise%3Fopen_modal_url%3D%252Fproducts%252Ftimextender%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fetl-tools%25252Fenterprise%2526source%253Dcategory&secure%5Btoken%5D=e329c0023c1915b593625771c2a7128defb49cd5b75662d0315ab3f30feb78ab&secure%5Burl%5D=https%3A%2F%2Fwww.cdata.com%2Fsync%2F%3Futm_source%3Dg2%26utm_medium%3Dsponsored-link%26utm_campaign%3Dsync-clicks-etl-tools&secure%5Burl_type%5D=custom_url)

### [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:** 1,326

#### 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:** 9.2/10 (Category avg: 8.7/10)
- **Auditing:** 8.5/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Databricks?

- **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc)
- **Company Website:** databricks.com
- **Year Founded:** 2013
- **HQ Location:** San Francisco, CA
- **Twitter:** @databricks  
92,269 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=bddca64732f61b923d96364e8c8eb35711aab4f98797cb00ab071ff24fbdd392&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3477522%2F&secure%5Burl_type%5D=linkedin_company_website)  
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% Large, 38% Medium

#### What Do G2 Reviewers Say About Databricks?

_AI-generated summary from verified user reviews_

##### Pros

- Users praise the **ease of use** and **comprehensive features** of Databricks for data warehousing and ML applications.
- Users praise the **ease of use** of Databricks, enhancing their experience with intuitive interfaces and reliable services.
- Users appreciate the **seamless integrations** of Databricks with AWS and other tools, enhancing daily operations and efficiency.
- Users value the **seamless collaboration** offered by Databricks, enhancing teamwork on data projects with real-time insights.
- Users praise the **integrated analytical features** of Databricks, enhancing collaborative data processing and insight visualization.

##### Cons

- Users note a **steep learning curve** initially, with confusing permissions and compute modes affecting usability.
- Users note that the **costs can be quite high** for utilizing Databricks effectively, especially for large data projects.
- Users find a **steep learning curve** with Databricks, especially challenging for newcomers to big data tools.
- Users find the **complexity** of Databricks challenging, especially for smaller teams and initial setup processes.
- Users face **complex setup** challenges initially, though support helps simplify the experience over time.

#### What Are Recent G2 Reviews of Databricks?

**["Databricks Streamlines ETL and Analytics with Scalable Notebooks"](https://www.g2.com/survey_responses/databricks-review-13181721)**

**Rating:** 5.0/5.0 stars

_— Diana C._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13181721)

**["Helpful for Managing and Analyzing Operational Data"](https://www.g2.com/survey_responses/databricks-review-13090803)**

**Rating:** 4.5/5.0 stars

_— Vishaka C._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13090803)

#### What Are G2 Users Discussing About Databricks?

- [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments, 1 upvote
- [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments
- [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 2 upvotes
- [What are the features of Databricks?](https://www.g2.com/discussions/what-are-the-features-of-databricks) - 4 comments, 2 upvotes

### [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:** 855

#### How Do G2 Users Rate Alteryx?

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10)
- **Automation:** 9.7/10 (Category avg: 9.0/10)
- **Scalability:** 10.0/10 (Category avg: 8.7/10)
- **Auditing:** 10.0/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Alteryx?

- **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx)
- **Company Website:** www.alteryx.com
- **Year Founded:** 1997
- **HQ Location:** Irvine, CA
- **Twitter:** @alteryx  
26,149 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ae8a7629c5a6d593caff29361a6ee3fb670df11992dd94a9656c66461078b340&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F903031%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,304 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Analyst, Analyst
- **Top Industries:** Financial Services, Accounting
- **Company Size:** 63% Large, 21% Medium

#### What Do G2 Reviewers Say About Alteryx?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Alteryx, finding it user-friendly and efficient for non-technical users.
- Users appreciate the **automation capabilities** of Alteryx, enhancing speed and efficiency in data preparation and analysis.
- Users love the **intuitive design** of Alteryx, making data management and workflow creation effortless and efficient.
- Users find Alteryx to be **very easy to learn and use** , enhancing their data workflow and automation experience.
- Users appreciate the **efficiency** of Alteryx, enabling quick data processing and streamlined workflows without complex coding.

##### Cons

- Users mention that Alteryx has a **high cost** which can be challenging for small teams and startups.
- Users find a **steep learning curve** for advanced features, making it challenging for beginners to master Alteryx quickly.
- Users point out the **missing features** in Alteryx, such as limited connectors and issues with output flexibility.
- Users find **learning difficulty** in Alteryx due to confusing tools and troubleshooting errors, especially for beginners.
- Users encounter **slow performance** when processing large datasets, impacting efficiency and usability in Alteryx.

#### What Are Recent G2 Reviews of Alteryx?

**["Scales Operations and Saves Time with Automated Data Workflows"](https://www.g2.com/survey_responses/alteryx-review-13047637)**

**Rating:** 4.5/5.0 stars

_— Ihor B._

[Read full review](https://www.g2.com/survey_responses/alteryx-review-13047637)

**["Makes Data Prep Faster with an Intuitive Drag-and-Drop Workflow"](https://www.g2.com/survey_responses/alteryx-review-13190742)**

**Rating:** 4.5/5.0 stars

_— Anushka S._

[Read full review](https://www.g2.com/survey_responses/alteryx-review-13190742)

### [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews)

BigQuery is an AI-ready, petabyte-scale, and cost-effective data warehouse that lets you run analytics over vast amounts of data in near real time. 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:** 1,144

#### How Do G2 Users Rate Google Cloud BigQuery?

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10)
- **Automation:** 8.8/10 (Category avg: 9.0/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Google Cloud BigQuery?

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google  
31,899,995 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
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% Large, 35% Medium

#### What Do G2 Reviewers Say About Google Cloud BigQuery?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Google Cloud BigQuery, enabling quick analysis of massive datasets without hassle.
- Users appreciate the **exceptional speed** of BigQuery, allowing for quick processing of large datasets seamlessly.
- Users love the **easy integration** with Google Cloud services, enabling smooth data analysis and management.
- Users appreciate the **fast querying capabilities** of Google Cloud BigQuery, allowing effortless analysis of massive datasets.
- Users appreciate the **query efficiency** of BigQuery, effortlessly processing complex queries on massive datasets with speed.

##### Cons

- Users find the **costs can escalate quickly** with Google Cloud BigQuery, requiring careful query optimization to manage expenses.
- Users struggle with **query issues** in BigQuery, facing rising costs and challenges in query optimization and troubleshooting.
- Users find **cost management challenging** with Google Cloud BigQuery due to unpredictable pricing and incidents of unexpected charges.
- Users experience **cost issues** with Google Cloud BigQuery, struggling with unexpected high bills and limited pricing visibility.
- Users find the **steep learning curve** of Google Cloud BigQuery challenging, particularly for advanced features and optimization techniques.

#### What Are Recent G2 Reviews of Google Cloud BigQuery?

**["Easy-to-Use Cloud Tool with Shareable, Saved Queries"](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)**

**Rating:** 4.0/5.0 stars

_— Reetika P._

[Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)

**["Scalable, Secure BigQuery That Connects Seamlessly Across Services"](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)**

**Rating:** 5.0/5.0 stars

_— Aayush M._

[Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)

#### What Are G2 Users Discussing About Google Cloud BigQuery?

- [Is Big Query free?](https://www.g2.com/discussions/is-big-query-free) - 3 comments, 1 upvote
- [Is BigQuery part of Google Cloud Platform?](https://www.g2.com/discussions/is-bigquery-part-of-google-cloud-platform) - 2 comments, 2 upvotes
- [What is Google BigQuery based on?](https://www.g2.com/discussions/what-is-google-bigquery-based-on) - 1 comment
- [What is Google BigQuery used for?](https://www.g2.com/discussions/what-is-google-bigquery-used-for) - 1 comment

### [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:** 114

#### 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:** 7.5/10 (Category avg: 8.7/10)
- **Auditing:** 7.2/10 (Category avg: 8.1/10)

#### Who Is the Company Behind IBM StreamSets?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
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% Large, 34% Medium

#### What Do G2 Reviewers Say About IBM StreamSets?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** in IBM StreamSets, highlighting its intuitive interface and beginner-friendly features.
- Users praise the **user-friendly drag-and-drop interface** of IBM StreamSets, enhancing visualization and debugging efficiency.
- Users value the **effective data management capabilities** of IBM StreamSets for seamless integration and automation across environments.
- Users appreciate the **simplification of data integration workflows** in IBM StreamSets, making pipeline creation intuitive and efficient.
- Users value the **wide range of integrations** offered by IBM StreamSets, enhancing cloud and on-premise data connectivity.

##### Cons

- Users experience a **steep learning curve** , particularly when using advanced features and managing complex pipelines effectively.
- Users find the **pricing to be excessive** , especially for smaller teams, impacting overall satisfaction with IBM StreamSets.
- Users find the **learning difficulty** of advanced features in StreamSets to be time-consuming and not well-supported.
- Users often experience **slow performance** with IBM StreamSets, particularly when processing large volumes of data or complex pipelines.
- Users find the **steep learning curve** of IBM StreamSets challenging, especially with advanced features and configurations.

#### What Are Recent G2 Reviews of IBM StreamSets?

**["Powerful Data Integration With IBM Stream sets."](https://www.g2.com/survey_responses/ibm-streamsets-review-11654909)**

**Rating:** 5.0/5.0 stars

_— Abhishek D._

[Read full review](https://www.g2.com/survey_responses/ibm-streamsets-review-11654909)

**["Simplifies Real-Time Data Pipelines with Mixed Customization"](https://www.g2.com/survey_responses/ibm-streamsets-review-12240946)**

**Rating:** 4.0/5.0 stars

_— Sravya A._

[Read full review](https://www.g2.com/survey_responses/ibm-streamsets-review-12240946)

#### What Are G2 Users Discussing About IBM StreamSets?

- [What is StreamSets used for?](https://www.g2.com/discussions/what-is-streamsets-used-for)
- [What is StreamSets data collector?](https://www.g2.com/discussions/what-is-streamsets-data-collector)
- [What is StreamSets control hub?](https://www.g2.com/discussions/what-is-streamsets-control-hub)
- [Are StreamSets free?](https://www.g2.com/discussions/are-streamsets-free)
- [What is StreamSets tool?](https://www.g2.com/discussions/what-is-streamsets-tool) - 1 comment

### [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews)

Azure Data Factory (ADF) is a fully managed, serverless data integration service designed to simplify the process of ingesting, preparing, and transforming data from diverse sources. It enables organizations to construct and orchestrate Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows in a code-free environment, facilitating seamless data movement and transformation across on-premises and cloud-based systems. Key Features and Functionality: - Extensive Connectivity: ADF offers over 90 built-in connectors, allowing integration with a wide array of data sources, including relational databases, NoSQL systems, SaaS applications, APIs, and cloud storage services. - Code-Free Data Transformation: Utilizing mapping data flows powered by Apache Spark™, ADF enables users to perform complex data transformations without writing code, streamlining the data preparation process. - SSIS Package Rehosting: Organizations can easily migrate and extend their existing SQL Server Integration Services (SSIS) packages to the cloud, achieving significant cost savings and enhanced scalability. - Scalable and Cost-Effective: As a serverless service, ADF automatically scales to meet data integration demands, offering a pay-as-you-go pricing model that eliminates the need for upfront infrastructure investments. - Comprehensive Monitoring and Management: ADF provides robust monitoring tools, allowing users to track pipeline performance, set up alerts, and ensure efficient operation of data workflows. Primary Value and User Solutions: Azure Data Factory addresses the complexities of modern data integration by providing a unified platform that connects disparate data sources, automates data workflows, and facilitates advanced data transformations. This empowers organizations to derive actionable insights from their data, enhance decision-making processes, and accelerate digital transformation initiatives. By offering a scalable, cost-effective, and code-free environment, ADF reduces the operational burden on IT teams and enables data engineers and business analysts to focus on delivering value through data-driven strategies.

**Average Rating:** 4.6/5.0

**Total Reviews:** 95

#### How Do G2 Users Rate Azure Data Factory?

- **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.1/10)
- **Automation:** 9.2/10 (Category avg: 9.0/10)
- **Scalability:** 9.1/10 (Category avg: 8.7/10)
- **Auditing:** 8.4/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Azure Data Factory?

- **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft)
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft  
13,091,739 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website)  
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% Large, 30% Medium

#### What Do G2 Reviewers Say About Azure Data Factory?

_AI-generated summary from verified user reviews_

##### Pros

- Users love the **seamless data integration** capabilities of Azure Data Factory, simplifying complex workflows and enhancing productivity.
- Users value the **ease of use** of Azure Data Factory, simplifying data integration with its low-code visual interface.
- Users appreciate the **seamless connectivity** of Azure Data Factory for integrating diverse data sources with minimal coding.
- Users value the **seamless integration capabilities** of Azure Data Factory, simplifying complex data workflows across various sources.
- Users value the **scalability** of Azure Data Factory, enabling them to effortlessly manage and integrate vast data sources.

##### Cons

- Users find the **debugging difficulty** in Azure Data Factory frustrating, particularly for complex pipelines and troubleshooting failures.
- Users find **difficult debugging** with Azure Data Factory, often facing challenges in troubleshooting complex pipelines effectively.
- Users find Azure Data Factory to be **expensive** due to unpredictable costs linked to pipeline executions and data movements.
- Users find the **feature limitations** of Azure Data Factory hinder their ability to efficiently monitor and integrate with Power BI.
- Users find Azure Data Factory's **complexity and limitations** challenging, particularly with debugging and managing intricate workflows.

#### What Are Recent G2 Reviews of Azure Data Factory?

**["Intuitive, Scalable Data Integration with Azure Data Factory"](https://www.g2.com/survey_responses/azure-data-factory-review-12454264)**

**Rating:** 4.5/5.0 stars

_— Alan R._

[Read full review](https://www.g2.com/survey_responses/azure-data-factory-review-12454264)

**["Low-Code Drag-and-Drop That Makes Development Easy for Developers and Business Users"](https://www.g2.com/survey_responses/azure-data-factory-review-12746463)**

**Rating:** 4.5/5.0 stars

_— Shyam s._

[Read full review](https://www.g2.com/survey_responses/azure-data-factory-review-12746463)

#### What Are G2 Users Discussing About Azure Data Factory?

- [Is Azure data Factory an ETL tool?](https://www.g2.com/discussions/is-azure-data-factory-an-etl-tool) - 2 comments
- [What are the additional capabilities of data Factory?](https://www.g2.com/discussions/what-are-the-additional-capabilities-of-data-factory)
- [Which 3 types of activities can you run in Microsoft Azure data Factory?](https://www.g2.com/discussions/which-3-types-of-activities-can-you-run-in-microsoft-azure-data-factory)
- [What does Azure data/factory do?](https://www.g2.com/discussions/what-does-azure-data-factory-do)

### [AWS Glue](https://www.g2.com/products/aws-glue/reviews)

AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application develop-ment. You can discover and connect to 70+ diverse data sources, manage your data in a centralized data catalog, and visually create, run, and monitor ETL pipelines to load data into your data lakes. You can im-mediately search and query catalogued data using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.

**Average Rating:** 4.3/5.0

**Total Reviews:** 194

#### How Do G2 Users Rate AWS Glue?

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10)
- **Automation:** 8.8/10 (Category avg: 9.0/10)
- **Scalability:** 8.9/10 (Category avg: 8.7/10)
- **Auditing:** 8.7/10 (Category avg: 8.1/10)

#### Who Is the Company Behind AWS Glue?

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
147,094 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% Large, 29% Medium

#### What Do G2 Reviewers Say About AWS Glue?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of AWS Glue, finding it simple and effective for ETL operations.
- Users appreciate the **seamless integration capabilities** of AWS Glue, enhancing data movement and analytics efficiency.
- Users appreciate the **fully managed ETL service** of AWS Glue, enjoying seamless integration and ease of use.
- Users love AWS Glue for its **simplified data preparation and rich features** , enhancing analytics and machine learning processes.
- Users appreciate the **ease of implementation** in AWS Glue, enhancing their experience in building data integration frameworks.

##### Cons

- Users experience **slow performance** with AWS Glue, noting long start-up times and complex debugging challenges.
- Users find **debugging difficult** due to unclear error messages and a steep learning curve with AWS Glue.
- Users face **difficult debugging** issues with AWS Glue due to unclear error messages and complex processes during job execution.
- Users experience **performance issues** with AWS Glue, noting slow startup times and challenging debugging processes.
- Users face **time-consuming startup and debugging processes** with AWS Glue, impacting efficiency and user experience.

#### What Are Recent G2 Reviews of AWS Glue?

**["Serverless ETL Made Easy with AWS Glue"](https://www.g2.com/survey_responses/aws-glue-review-12864874)**

**Rating:** 5.0/5.0 stars

_— mani s._

[Read full review](https://www.g2.com/survey_responses/aws-glue-review-12864874)

**["AWS Glue Makes ETL Simple with Serverless Scalability and Deep AWS Integration"](https://www.g2.com/survey_responses/aws-glue-review-12380790)**

**Rating:** 4.5/5.0 stars

_— Pradip G._

[Read full review](https://www.g2.com/survey_responses/aws-glue-review-12380790)

#### What Are G2 Users Discussing About AWS Glue?

- [What is AWS Glue and how it works?](https://www.g2.com/discussions/what-is-aws-glue-and-how-it-works) - 1 comment
- [What does AWS Glue do?](https://www.g2.com/discussions/what-does-aws-glue-do) - 2 comments
- [What are the main components of AWS Glue?](https://www.g2.com/discussions/what-are-the-main-components-of-aws-glue) - 2 comments
- [What are the features of glue?](https://www.g2.com/discussions/what-are-the-features-of-glue) - 1 comment

### [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:** 1,036

#### 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:** 7.3/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Domo?

- **Seller:** [Domo](https://www.g2.com/sellers/domo)
- **Company Website:** www.domo.com
- **Year Founded:** 2010
- **HQ Location:** American Fork, UT
- **Twitter:** @Domotalk  
63,513 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=930264e423425693f202ced16a30f6d197bcd60a8bf42ced6ba13de91b09312c&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F25237%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,299 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Analyst, Business Analyst
- **Top Industries:** Computer Software, Marketing and Advertising
- **Company Size:** 49% Medium, 28% Large

#### What Do G2 Reviewers Say About Domo?

_AI-generated summary from verified user reviews_

##### Pros

- Users value Domo's **ease of use** , making it accessible for all, even those who aren't tech-savvy.
- Users value the **flexible dashboards** in Domo, allowing seamless data visualization from various sources.
- Users find Domo's **intuitive design** enhances data handling and decision-making, making it accessible for all skill levels.
- Users praise Domo for its **easy integrations** , enabling seamless data connections and enhancing data management efficiency.
- Users value the **seamless integration** capabilities of Domo, enhancing data management across various platforms and sources.

##### Cons

- Users find the **learning curve challenging** with Domo, often requiring dedicated resources to manage updates and functionalities.
- Users struggle with **missing features** in Domo, including outdated systems and limited capabilities in visualizations and connectors.
- Users are frustrated by **data management issues** , including upload adjustments and poor organization of datasets in Domo.
- Users find Domo to be **expensive** due to high costs associated with features and external consulting needs.
- Users find Domo's **complexity** overwhelming, requiring technical expertise and extensive setup that complicate the user experience.

#### What Are Recent G2 Reviews of Domo?

**["Domo Turns Disconnected Reports Into a Game-Changing Sales Scorecard"](https://www.g2.com/survey_responses/domo-review-13128007)**

**Rating:** 5.0/5.0 stars

_— Renee G._

[Read full review](https://www.g2.com/survey_responses/domo-review-13128007)

**["Fast, Reliable Dashboarding with Quick Data Connections in Domo"](https://www.g2.com/survey_responses/domo-review-13150907)**

**Rating:** 4.5/5.0 stars

_— Katie S._

[Read full review](https://www.g2.com/survey_responses/domo-review-13150907)

#### What Are G2 Users Discussing About Domo?

- [What is Domo used for?](https://www.g2.com/discussions/what-is-domo-used-for) - 1 comment
- [How much does Domo cost?](https://www.g2.com/discussions/how-much-does-domo-cost)
- [What is Domo data?](https://www.g2.com/discussions/what-is-domo-data)
- [Is Domo any good?](https://www.g2.com/discussions/is-domo-any-good)
- [What does Domo software do?](https://www.g2.com/discussions/what-does-domo-software-do)

### [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:** 166

#### 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:** 8.0/10 (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:** www.ibm.com
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, CEO
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 33% Small, 32% Large

#### What Do G2 Reviewers Say About IBM watsonx.data?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of IBM watsonx.data, finding it reliable and efficient for data management tasks.
- Users value the **organized data integration** and intuitive interface of IBM watsonx.data, enhancing efficiency and analytics.
- Users value the **organized and efficient data management** of IBM watsonx.data, enhancing analytics and reporting tasks seamlessly.
- Users value the **seamless data source integration** in IBM watsonx.data, enhancing flexibility and efficiency for diverse projects.
- Users value the **ability to unify data across hybrid environments** , enhancing flexibility and driving informed decision-making.

##### Cons

- Users find the **learning curve steep** , making initial setup and navigation challenging for newcomers to IBM watsonx.data.
- Users find the **complexity** of setting up IBM watsonx.data a barrier, especially for newcomers to IBM technologies.
- Users find the **pricing steep** for IBM watsonx.data, making it less accessible for smaller businesses and projects.
- Users find the **difficult setup** of IBM watsonx.data time-consuming, with a steep learning curve and complex configurations.
- Users find IBM watsonx.data **difficult to navigate** , especially for beginners and those unfamiliar with AI and data analytics.

#### What Are Recent G2 Reviews of IBM watsonx.data?

**["Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve"](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)**

**Rating:** 4.0/5.0 stars

_— Arkajit D._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)

**["Unified Data Management with Learning Curve"](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742)**

**Rating:** 5.0/5.0 stars

_— Anchal P._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12817742)

### [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:** 1,065

#### 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)
- **Auditing:** 10.0/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Celigo?

- **Seller:** [Celigo](https://www.g2.com/sellers/celigo)
- **Company Website:** www.celigo.com
- **Year Founded:** 2011
- **HQ Location:** Redwood City, California
- **Twitter:** @celigoinc  
1,418 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=62d4b59e1d0308da646469c5a274beead8dbe6d3770aa75cd23cfb98ce47b859&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F275831%2F&secure%5Burl_type%5D=linkedin_company_website)  
786 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** IT Manager, NetSuite Administrator
- **Top Industries:** Retail, Consumer Goods
- **Company Size:** 58% Medium, 37% Small

#### What Do G2 Reviewers Say About Celigo?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** in Celigo, making integration management accessible for everyone, regardless of technical background.
- Users value the **user-friendly integrations** of Celigo, appreciating its customizable solutions for diverse client needs.
- Users value the **integration capabilities** of Celigo, enabling seamless connections with various APIs easily and efficiently.
- Users value the **easy integrations** of Celigo, enabling seamless connectivity and enhanced functionality across systems.
- Users value the **helpful and thorough customer support** provided by Celigo, ensuring effective assistance with customizations.

##### Cons

- Users find **error handling challenging** with unclear messages and random issues that are difficult to track.
- Users often remark on the **premium pricing** of Celigo, with costs increasing as more features are added.
- Users find the **learning curve steep** , requiring time and effort to fully understand the platform's functionalities.
- Users often face **complexity challenges** with Celigo, struggling with vague error messages and intricate integration processes.
- Users report **premium pricing** can be confusing, especially with unexpected increases in contract renewals.

#### What Are Recent G2 Reviews of Celigo?

**["Seamless Integration with Exceptional Support"](https://www.g2.com/survey_responses/celigo-review-1996577)**

**Rating:** 5.0/5.0 stars

_— Steve B._

[Read full review](https://www.g2.com/survey_responses/celigo-review-1996577)

**["A trusted integration partner for Shopify and ERP projects"](https://www.g2.com/survey_responses/celigo-review-13172761)**

**Rating:** 5.0/5.0 stars

_— Sergiu T._

[Read full review](https://www.g2.com/survey_responses/celigo-review-13172761)

#### What Are G2 Users Discussing About Celigo?

- [What is Celigo used for?](https://www.g2.com/discussions/what-is-celigo-used-for)

### [Workato](https://www.g2.com/products/workato/reviews)

Workato is the #1-rated iPaaS and the leader in Enterprise MCP — the platform enterprises trust to unify integration, automation, and AI in one secure, cloud-native runtime. Trusted by over 12,000 customers including half the Fortune 500, Workato connects every system, process, and data source with 14,000+ pre-built connectors. What sets Workato apart: Enterprise MCP turns proven business processes into governed, agent-ready skills that any AI agent — Claude, ChatGPT, Cursor, or custom-built — can execute safely and predictably. No rip-and-replace required. Whether modernizing legacy integrations or deploying agentic AI at scale, Workato delivers the orchestration, governance, and trust needed in the enterprise.

**Average Rating:** 4.7/5.0

**Total Reviews:** 749

#### How Do G2 Users Rate Workato?

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10)
- **Automation:** 9.2/10 (Category avg: 9.0/10)
- **Scalability:** 9.0/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Workato?

- **Seller:** [Workato](https://www.g2.com/sellers/workato)
- **Company Website:** www.workato.com
- **Year Founded:** 2013
- **HQ Location:** Mountain View, California
- **Twitter:** @Workato  
3,641 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=229b7e77382a8d2c3a0aeebe68dfc2316ea2caa6dd5d95ed0ee0d08884e6fc88&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3675685&secure%5Burl_type%5D=linkedin_company_website)  
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% Medium, 33% Large

#### What Do G2 Reviewers Say About Workato?

_AI-generated summary from verified user reviews_

##### Pros

- Users find Workato to be **user-friendly and efficient** , allowing easy automation without technical expertise.
- Users love the **easy integrations** offered by Workato, making automation between tools simple and efficient.
- Users value the **ease of integrations** with Workato, appreciating its user-friendly interface and extensive pre-built connectors.
- Users appreciate Workato's **user-friendly design and automation capabilities** , enhancing productivity and simplifying complex workflows.
- Users love the **ease of automation** in Workato, saving hours by effortlessly integrating various tools and systems.

##### Cons

- Users find the **complexity** of Workato daunting, especially regarding terminology and pricing structures that confuse newcomers.
- Users find the **learning curve steep** , with complex workflows and overwhelming onboarding complicating initial use.
- Users express frustration over **data limitations** in Workato, hindering email sends and file transfers for larger tasks.
- Users find the **limited application library** of Workato restrictive, requiring manual setup for less common integrations.
- Users face a **steep learning curve** with Workato, finding onboarding and initial setup quite overwhelming and complex.

#### What Are Recent G2 Reviews of Workato?

**["Workato helps us building complex integrations at lightning speed."](https://www.g2.com/survey_responses/workato-review-10305521)**

**Rating:** 5.0/5.0 stars

_— Sreenath B._

[Read full review](https://www.g2.com/survey_responses/workato-review-10305521)

**["The Platform That Grew With Us"](https://www.g2.com/survey_responses/workato-review-12941177)**

**Rating:** 5.0/5.0 stars

_— Anshu b._

[Read full review](https://www.g2.com/survey_responses/workato-review-12941177)

#### What Are G2 Users Discussing About Workato?

- [What does Workato do?](https://www.g2.com/discussions/what-does-workato-do)
- [How much does Workato cost?](https://www.g2.com/discussions/how-much-does-workato-cost) - 1 comment
- [What is a Workato recipe?](https://www.g2.com/discussions/what-is-a-workato-recipe) - 3 comments
- [What is Workato used for?](https://www.g2.com/discussions/what-is-workato-used-for)

### [Boomi Data Integration](https://www.g2.com/products/boomi-data-integration/reviews)

Rivery's SaaS platform provides a unified solution for ELT pipelines, workflow orchestration, and data operations. Achieve more with less and create the most efficient, scalable data stack for your organization. Some of Rivery's features and capabilities: - Completely Automated SaaS Platform: Get setup and start connecting data in the Rivery platform in just a few minutes with little to no maintenance required. - Unified Data Ingestion, Transformation, & Orchestration: 100% data source capability, insight-ready data with both SQL and Python transformations, and complete workflow automation. - 200+ Native Connectors: Instantly connect to applications, databases, file storage options, and data warehouses with our fully-managed and always up-to-date connectors, including BigQuery, Redshift, Shopify, Snowflake, Amazon S3, Firebolt, Databricks, Salesforce, MySQL, PostgreSQL, and Rest API to name just a few. - Python Support: Have a data source that requires custom code? With Rivery’s native Python support, you can pull data from any system, no matter how complex the need. - Change Data Capture/Data Replication: Rivery’s best-in-class CDC support provides an easy, reliable and fast solution for replicating data from a database to your data warehouse. - 1-Click Data Apps: With Rivery Kits, deploy complete, production-level workflow templates in minutes with data models, pipelines, transformations, table schemas, and orchestration logic already defined for you based on best practices. - Data Development Lifecycle Support: Separate walled-off environments for each stage of your development, from dev and staging to production, making it easier to move fast without breaking things. Get version control, API, & CLI included. - Data Operations: With Rivery, you get centralized logging & reporting, monitoring & alerts, and data quality as part of a robust data operations layer for your data pipelines. - Solution-Led Support: Consistently rated the best support by G2, receive engineering-led assistance from Rivery to facilitate all your data needs. - Data Security: Industry-leading security and enterprise-grade privacy standards are built into Rivery’s network, product, and policies.

**Average Rating:** 4.7/5.0

**Total Reviews:** 120

#### How Do G2 Users Rate Boomi Data Integration?

- **Has the product been a good partner in doing business?:** 9.6/10 (Category avg: 9.1/10)
- **Automation:** 9.5/10 (Category avg: 9.0/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 8.8/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Boomi Data Integration?

- **Seller:** [Boomi](https://www.g2.com/sellers/boomi)
- **Year Founded:** 2000
- **HQ Location:** Conshohocken, PA
- **Twitter:** @boomi  
101,014 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=48e58db8d91e1da54d6b476d5f5c5a2d98aab91fa1d98184cfcc08cb78bcfd9d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fboomi-inc%2F&secure%5Burl_type%5D=linkedin_company_website)  
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% Medium, 36% Small

#### What Do G2 Reviewers Say About Boomi Data Integration?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **user-friendly interface** of Boomi Data Integration, making it easy to learn and implement.
- Users commend the **excellent customer support** of Boomi Data Integration, enhancing their implementation and overall experience.
- Users value the **wide range of connectors** in Boomi Data Integration, simplifying data connection and reporting across platforms.
- Users value the **automation capabilities** of Boomi Data Integration, significantly enhancing their ETL processes and workflow efficiency.
- Users appreciate the **ease of implementation** with Boomi Data Integration, highlighting user-friendliness and excellent support during setup.

##### Cons

- Users face **data limitations** with Boomi Data Integration, often lacking necessary fields and documentation when connecting to sources.
- Users often face **information deficiency** due to missing documentation and unavailable fields, complicating their data integration efforts.
- Users experience **insufficient information** when connecting to data sources, leading to challenges in accessing necessary fields.
- Users find Boomi Data Integration **lacking features** , often facing missing documentation and unavailable report fields during data connections.
- Users find the **limited features** of Boomi Data Integration frustrating, as necessary fields in reports may be unavailable.

#### What Are Recent G2 Reviews of Boomi Data Integration?

**["Actual review of ELT Tool Rivery"](https://www.g2.com/survey_responses/boomi-data-integration-review-10179408)**

**Rating:** 5.0/5.0 stars

_— Amit K._

[Read full review](https://www.g2.com/survey_responses/boomi-data-integration-review-10179408)

**["Boomi Data Integration: Fast, Reliable Integrations at Scale"](https://www.g2.com/survey_responses/boomi-data-integration-review-12546768)**

**Rating:** 5.0/5.0 stars

_— Takkellapati S._

[Read full review](https://www.g2.com/survey_responses/boomi-data-integration-review-12546768)

#### What Are G2 Users Discussing About Boomi Data Integration?

- [What advice do you have for others considering Rivery for data integration and pipeline management?](https://www.g2.com/discussions/what-advice-do-you-have-for-others-considering-rivery-for-data-integration-and-pipeline-management)
- [What is the use of Rivery?](https://www.g2.com/discussions/what-is-the-use-of-rivery) - 2 comments
- [How much does Rivery cost?](https://www.g2.com/discussions/how-much-does-rivery-cost) - 1 comment
- [What does Rivery do?](https://www.g2.com/discussions/what-does-rivery-do) - 1 comment

### [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:** 373

#### 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:** www.snaplogic.com
- **Year Founded:** 2006
- **HQ Location:** San Mateo, CA
- **Twitter:** @SnapLogic  
7,348 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=5261a75f1a744444604a852bca79d92e4b9b8336bca6cd31b6688370561a9346&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F210766%2F&secure%5Burl_type%5D=linkedin_company_website)  
307 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Consultant
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 47% Large, 36% Medium

#### What Do G2 Reviewers Say About SnapLogic Intelligent Integration Platform (IIP)?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of SnapLogic, allowing quick integration and straightforward pipeline setup.
- Users appreciate the **easy integrations** of SnapLogic, benefiting from a user-friendly interface and various connectors.
- Users appreciate the **seamless integration** capabilities of SnapLogic IIP, enabling efficient connections across diverse systems.
- Users enjoy the **user-friendly interface** of SnapLogic, simplifying tasks and enhancing overall productivity.
- Users love the **simplicity of automation** in SnapLogic IIP, enabling faster development and efficient integration processes.

##### Cons

- Users report **performance issues** with SnapLogic, especially under heavy workloads and in load balancing functionality.
- Users experience **poor performance** under heavy workloads, leading to frustration with debugging and complex integrations.
- Users struggle with **technical difficulties** , including debugging challenges and performance drops during heavy workloads.
- Users find the **complexity of understanding Snaps** and tracing errors to be quite challenging in SnapLogic IIP.
- Users report **poor error reporting** and lack of clarity in debugging, complicating the troubleshooting process.

#### What Are Recent G2 Reviews of SnapLogic Intelligent Integration Platform (IIP)?

**["Fast and Flexible Integrations Powered by Pre-Built Snaps, Visual Workflows, and Great Support"](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13181168)**

**Rating:** 5.0/5.0 stars

_— aravind k._

[Read full review](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13181168)

**["Effortless Integration, Minor Long-Run Hiccups"](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-10786237)**

**Rating:** 4.0/5.0 stars

_— Sayeedul R._

[Read full review](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-10786237)

#### What Are G2 Users Discussing About SnapLogic Intelligent Integration Platform (IIP)?

- [What is SnapLogic Intelligent Integration Platform (IIP) used for?](https://www.g2.com/discussions/what-is-snaplogic-intelligent-integration-platform-iip-used-for) - 1 comment

### [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:** 120

#### 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:** 8.7/10 (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:** www.matillion.com
- **Year Founded:** 2011
- **HQ Location:** Salford, GB
- **Twitter:** @matillion  
7,362 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9b553fae1e51bb2b58491b1c1d561a15b7dd370d485b1ff7affe8e7cbd75e1cf&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2360297%2F&secure%5Burl_type%5D=linkedin_company_website)  
463 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 47% Medium, 31% Large

#### What Do G2 Reviewers Say About Maia?

_AI-generated summary from verified user reviews_

##### Pros

- Users find the **ease of use** in Maia's interface invaluable for seamless ETL configuration and understanding.
- Users appreciate the **seamless automation** of Matillion, making ETL processes effortless and efficient across platforms.
- Users appreciate the **simple UI** of Matillion, which makes configuration easy and user-friendly for everyone.
- Users love Matillion's **intuitive and simple UI** , making it easy for beginners to configure and navigate.
- Users commend Maia for its **ETL efficiency** , making complex workflows user-friendly and scalable for all levels of analysts.

##### Cons

- Users experience **job performance issues** due to the limitations of the Jython interpreter and single-thread workflows.
- Users find the **pricing model expensive** , especially as data volume increases, impacting overall affordability.
- Users report **job performance issues** with the Jython interpreter and single-thread workflow limitations affecting efficiency.
- Users express concern over **cloud dependency** , feeling locked into the environment with limited customization options.
- Users find **API limitations** in Maia frustrating, as administrative features lack sufficient access and usability options.

#### What Are Recent G2 Reviews of Maia?

**["Maia Makes Onboarding Fast with an Intuitive UI and Low-Code Pipelines"](https://www.g2.com/survey_responses/maia-review-12942268)**

**Rating:** 4.5/5.0 stars

_— Anthony S._

[Read full review](https://www.g2.com/survey_responses/maia-review-12942268)

**["Maia Scaled 800+ Pipeline Migrations Without Added Overhead"](https://www.g2.com/survey_responses/maia-review-12920298)**

**Rating:** 5.0/5.0 stars

_— Keith G._

[Read full review](https://www.g2.com/survey_responses/maia-review-12920298)

#### What Are G2 Users Discussing About Maia?

- [What is Matillion ETL used for?](https://www.g2.com/discussions/what-is-matillion-etl-used-for) - 1 comment
- [What is Matillion Data Loader used for?](https://www.g2.com/discussions/what-is-matillion-data-loader-used-for)
- [What are ETL tools used for?](https://www.g2.com/discussions/what-are-etl-tools-used-for)
- [Is Matillion open source?](https://www.g2.com/discussions/is-matillion-open-source)
- [What is ETL in software?](https://www.g2.com/discussions/what-is-etl-in-software)

### [Fivetran](https://www.g2.com/products/fivetran/reviews)

Fivetran is the data foundation for AI. One platform moves, manages, and transforms data from every application, database, event stream, and file your business runs on into a governed foundation that analytics, operations, and AI can act on. Connectors deploy in minutes, run themselves, and adjust automatically when a source changes, so your data team spends its time building, not maintaining pipelines.

**Average Rating:** 4.3/5.0

**Total Reviews:** 805

#### How Do G2 Users Rate Fivetran?

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10)
- **Automation:** 8.9/10 (Category avg: 9.0/10)
- **Scalability:** 8.5/10 (Category avg: 8.7/10)
- **Auditing:** 7.3/10 (Category avg: 8.1/10)

#### Who Is the Company Behind Fivetran?

- **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran)
- **Company Website:** www.fivetran.com
- **Year Founded:** 2012
- **HQ Location:** Oakland, CA
- **Twitter:** @fivetran  
5,767 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7f1ca0a984cd3b7fe678e6cf023235ee7978629644faf3910a5df7f92b63eea3&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ffivetran%2F&secure%5Burl_type%5D=linkedin_company_website)  
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% Medium, 27% Small

#### What Do G2 Reviewers Say About Fivetran?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Fivetran, enjoying seamless integration and effortless maintenance post-setup.
- Users appreciate the **easy setup** of Fivetran, making it straightforward to integrate with existing applications.
- Users value the **easy integration** of Fivetran, enabling seamless connectivity with various applications and tools.
- Users value the **responsive customer support** from Fivetran, enhancing their overall experience and satisfaction.
- Users appreciate the **intuitive and simple layout** of Fivetran, making data management effortless and enjoyable.

##### Cons

- Users experience **sync issues** with sporadic failures and confusion over usage quotas, complicating their workflow.
- Users note that Fivetran's pricing is **quite expensive** , which limits accessibility for many potential users.
- Users face **integration issues** with Fivetran, especially regarding schema ownership and modifying connections efficiently.
- Users find the **learning curve steep** , requiring significant technical knowledge to effectively navigate the system initially.
- Users consider Fivetran's **pricing issues** a barrier, wishing for lower costs and more flexible options for accessibility.

#### What Are Recent G2 Reviews of Fivetran?

**["No-Code, Self-Monitoring Pipelines with Connectors That Just Work"](https://www.g2.com/survey_responses/fivetran-review-13137995)**

**Rating:** 5.0/5.0 stars

_— Umesh ._

[Read full review](https://www.g2.com/survey_responses/fivetran-review-13137995)

**["Fast, Reliable No-Code Data Integrations with Huge ROI"](https://www.g2.com/survey_responses/fivetran-review-13138238)**

**Rating:** 4.5/5.0 stars

_— Jose Maria P._

[Read full review](https://www.g2.com/survey_responses/fivetran-review-13138238)

#### What Are G2 Users Discussing About Fivetran?

- [What is Fivetran used for?](https://www.g2.com/discussions/fivetran-what-is-fivetran-used-for) - 1 comment
- [What is Census used for?](https://www.g2.com/discussions/what-is-census-used-for)
- [Who owns Fivetran?](https://www.g2.com/discussions/who-owns-fivetran)
- [How much does Fivetran cost?](https://www.g2.com/discussions/how-much-does-fivetran-cost) - 1 comment
- [Is Fivetran an ETL tool?](https://www.g2.com/discussions/is-fivetran-an-etl-tool) - 2 comments

### [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:** 208

#### How Do G2 Users Rate dbt?

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10)
- **Automation:** 9.4/10 (Category avg: 9.0/10)
- **Scalability:** 9.2/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)

#### Who Is the Company Behind dbt?

- **Seller:** [dbt Labs](https://www.g2.com/sellers/dbt-labs)
- **Year Founded:** 2016
- **HQ Location:** Philadelphia, US
- **Twitter:** @getdbt  
14,792 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=2528ac46bc91e3acc7ad9e4f602bdecf43b7a29cef8c7a88fcb0b299043e4e1a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdbtlabs%2F&secure%5Burl_type%5D=linkedin_company_website)  
874 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Analytics Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 56% Medium, 27% Small

#### What Do G2 Reviewers Say About dbt?

_AI-generated summary from verified user reviews_

##### Pros

- Users love the **ease of use** of dbt, thanks to its clear structure, intuitive documentation, and seamless integration.
- Users value dbt for its **integration of software engineering best practices** , enhancing maintainability and collaboration in SQL transformations.
- Users value the **automation** features of dbt, significantly enhancing SQL code maintainability and transforming data workflows.
- Users value the **transformative power** of dbt, efficiently organizing and modeling data for actionable insights.
- Users value dbt for its **high data quality** , ensuring integrity and enhancing analytics workflows through modularization and documentation.

##### Cons

- Users face challenges with **limited functionality** in dbt due to rigid models and debugging difficulties, affecting project progress.
- Users often face **dependency issues** with dbt, leading to time-consuming troubleshooting and disruption in workflows.
- Users find the **steep learning curve** of mastering concepts like Jinja and Git to be quite challenging.
- Users struggle with **unhelpful error messages** in dbt, making troubleshooting difficult and frustrating.
- Users face **confusing error reporting** that complicates troubleshooting and hinders quick identification of issues.

#### What Are Recent G2 Reviews of dbt?

**["dbt Streamlines Data Pipelines with Powerful Incremental and SCD2 Features"](https://www.g2.com/survey_responses/dbt-review-12712114)**

**Rating:** 5.0/5.0 stars

_— Hithesh P._

[Read full review](https://www.g2.com/survey_responses/dbt-review-12712114)

**["Simple SQL-Driven Materializations with Powerful Lineage"](https://www.g2.com/survey_responses/dbt-review-12985641)**

**Rating:** 5.0/5.0 stars

_— Anish G._

[Read full review](https://www.g2.com/survey_responses/dbt-review-12985641)

#### What Are G2 Users Discussing About dbt?

- [What is DBT data Modelling?](https://www.g2.com/discussions/what-is-dbt-data-modelling) - 2 comments
- [What is DBT technology?](https://www.g2.com/discussions/what-is-dbt-technology) - 2 comments
- [What is DBT database tool?](https://www.g2.com/discussions/what-is-dbt-database-tool) - 1 comment
- [What is DBT tool used for?](https://www.g2.com/discussions/what-is-dbt-tool-used-for) - 2 comments

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Similar Categories

- [Big Data Integration Platforms](/categories/big-data-integration-platforms)
- [Cloud Migration](/categories/cloud-migration)
- [Embedded Integration Platforms](/categories/embedded-integration-platforms)

- [Enterprise Service Bus (ESB)](/categories/enterprise-service-bus-esb)
- [iPaaS](/categories/ipaas)
- [Reverse ETL](/categories/reverse-etl)

- [Stream Analytics](/categories/stream-analytics)

[Browse ETL Tools Themes](/categories/etl-tools/themes)

 ![Shalaka Joshi](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shalaka Joshi")
SJ

Researched and written by [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)

Updated 

Products classified in the overall ETL Tools category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business ETL Tools to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Enterprise Business ETL Tools category.

In addition to qualifying for inclusion in the ETL Tools category, to qualify for inclusion in the Enterprise Business ETL Tools category, a product must have at least 10 reviews left by a reviewer from an enterprise business.

Top Tools at a Glance

| 

 | 

Unified lakehouse pipelines with governance and ML workflows

 | 

User Review

"Databricks Streamlines ETL and Analytics with Scalable Notebooks"

 |
| 

 | 

NetSuite-centered app integration and sync

 | 

User Review

"A trusted integration partner for Shopify and ERP projects"

 |
| 

 | 

Drag-and-drop data prep and reporting automation

 | 

User Review

"Scales Operations and Saves Time with Automated Data Workflows"

 |
| 

 | 

Serverless analytics on large cloud datasets

 | 

User Review

"Easy-to-Use Cloud Tool with Shareable, Saved Queries"

 |
| 

 | 

Geospatial and multi-format data transformation

 | 

User Review

"FME Saves Time with Powerful GIS ETL and Automation"

 |
| 

 | 

Self-service ETL feeding business dashboards

 | 

User Review

"Domo Turns Disconnected Reports Into a Game-Changing Sales Scorecard"

 |
| 

 | 

Managed connector-based data ingestion

 | 

User Review

"No-Code, Self-Monitoring Pipelines with Connectors That Just Work"

 |
| 

 | 

Lakehouse querying across object storage

 | 

User Review

"Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve"

 |
| 

 | 

Low-code workflow automation across SaaS apps

 | 

User Review

"Workato helps us building complex integrations at lightning speed."

 |
| 

 | 

Visual enterprise integration across complex systems

 | 

User Review

"Effortless Integration, Minor Long-Run Hiccups"

 |

* * *

Show More

* * *

## 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