# Best Machine Learning Data Catalog Software

## How Many Machine Learning Data Catalog Software Products Does G2 Track?

**Total Products under this Category:** 89

### Category Stats (Aug 2026)

- **Average Rating:** 4.37/5 (↑0.01 vs Jul 2026) The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** BMC AMI Data (+0.44%) - Among all products in this category, BMC AMI Data recorded the largest rating increase compared to last month

_Last updated: August 01, 2026_

## How Does G2 Rank Machine Learning Data Catalog Software Products?

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

- 30 Analysts and Data Experts
- 1,800+ Authentic Reviews
- 89+ 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 Machine Learning Data Catalog Software
 ![G2 Grid® for Machine Learning Data Catalog Software plotting products by satisfaction and market presence](https://www.g2.com/categories/machine-learning-data-catalog/grids.png?focus%5B%5D=108031&focus%5B%5D=40849&focus%5B%5D=35126&focus%5B%5D=113991&focus%5B%5D=111980&focus%5B%5D=91379&focus%5B%5D=39669&focus%5B%5D=1886)

Highlighted products: Atlan, AWS Glue, Alation, Google Cloud Data Catalog, erwin Data Modeler, Appen, Collibra, and Cloudera.

Underlying data: [Grid® JSON](https://www.g2.com/categories/machine-learning-data-catalog/grids.json?focus%5B%5D=atlan&focus%5B%5D=aws-glue&focus%5B%5D=alation&focus%5B%5D=google-cloud-data-catalog&focus%5B%5D=quest-software-erwin-data-modeler&focus%5B%5D=appen&focus%5B%5D=collibra&focus%5B%5D=cloudera)

**Sponsored**

### Google Cloud BigQuery

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.

[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=1383&secure%5Bchosen_at%5D=2026-08-01T14%3A18%3A36Z&secure%5Bdisplayable_resource_id%5D=1661&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=neighbor_category&secure%5Bplacement_resource_ids%5D%5B%5D=1661&secure%5Bplacement_resource_ids%5D%5B%5D=2686&secure%5Bplacement_resource_ids%5D%5B%5D=1003209&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=6073&secure%5Bresource_id%5D=1383&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fmachine-learning-data-catalog&secure%5Btoken%5D=b5acd64a952a610cc5257f238ef46d441c2ffe73b672fad2d824bc7ac58024be&secure%5Burl%5D=https%3A%2F%2Fcloud.google.com%2Fbigquery%3Futm_source%3DG2%26utm_medium%3Ddisplay%26utm_campaign%3DCloud-SS-DR-GCP-1713658-GCP-DR-NA-US-en-G2-Display-Banner-All-%2525epid%21-%2525ecid%21-bigquery%26utm_content%3D%257Bdevice%257D-%257Badgroupid%257D-%257Bnetwork%257D-%257Btargetid%257D-%257Bloc_physical_ms%257D-%257Bcampaignid%257D&secure%5Burl_type%5D=custom_url)

### [Atlan](https://www.g2.com/products/atlan/reviews)

Atlan is the context layer for enterprise AI. It continuously reads your warehouses, databases, pipelines, BI tools, and business systems to reverse construct an enterprise data graph that captures assets, lineage, entities, metrics, policies, and relationships. On top of that graph, it enriches and curates machine-readable semantics — descriptions, popular joins, KPI and metric definitions, ontologies, and business rules — and organizes them into governed, versioned context repos: bounded bundles of context that reflect how your company defines key concepts and makes decisions. These context repos are then exposed through open interfaces (SQL, APIs, SDKs, OSI/MCP-style protocols) so that agents, copilots, and AI applications can call the same trusted context in real time, rather than each team hard-coding its own logic. Human-on-the-loop governance workflows for conflict resolution, deprecation, feedback, and certification keep that context trustworthy as the business, data, and models evolve.

**Average Rating:** 4.5/5.0

**Total Reviews:** 132

#### How Do G2 Users Rate Atlan?

- **Ease of Use:** 8.9/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 9.2/10 (Category avg: 8.6/10)
- **Metadata Management :** 9.4/10 (Category avg: 8.4/10)
- **Data Lineage:** 9.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Atlan?

- **Seller:** [Atlan](https://www.g2.com/sellers/atlan)
- **Company Website:** www.atlan.com
- **Year Founded:** 2019
- **HQ Location:** New York, US
- **Twitter:** @AtlanHQ  
9,804 Twitter followers
- **LinkedIn® Page:** [in.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=76bdd8566f32b170e53cfee476c7ff510e111497aa6c737d48bedd8b767b15e1&secure%5Burl%5D=https%3A%2F%2Fin.linkedin.com%2Fcompany%2Fatlan-hq&secure%5Burl_type%5D=linkedin_company_website)  
558 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Financial Services, Information Technology and Services
- **Company Size:** 51% Medium, 42% Large

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

_AI-generated summary from verified user reviews_

##### Pros

- Users commend Atlan for its **ease of use** , enabling smooth data collaboration and making data management accessible to everyone.
- Users value Atlan's **powerful data discovery and collaboration features** , enhancing data quality, governance, and accessibility.
- Users value the **seamless collaboration** with Atlan, enhancing data understanding and team efficiency across organizations.
- Users appreciate the **superior data cataloging** capabilities of Atlan, enhancing data discovery and collaboration effortlessly.
- Users appreciate the **easy setup** of Atlan, which enhances collaboration and streamlines workflows effortlessly.

##### Cons

- Users face **integration issues** with Atlan, particularly with Teams and non-native database setups requiring complex configurations.
- Users experience significant **dependency issues** in Atlan, hindering functionality and complicating automated updates and integrations.
- Users note the **limited customization** of Atlan, wishing for more flexibility to suit diverse team workflows.
- Users experience **slow technical support** and inaccuracies in resolutions, impacting their overall satisfaction with Atlan.
- Users experience **limited customization and technical complexity** in Atlan's UI, making it challenging for non-technical users.

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

**["Visual Design, Collaboration, and Outstanding Customer Support"](https://www.g2.com/survey_responses/atlan-review-13191535)**

**Rating:** 4.5/5.0 stars

_— Verified User in Transportation/Trucking/Railroad_

[Read full review](https://www.g2.com/survey_responses/atlan-review-13191535)

**["Atlan as a Central Metadata Hub with Powerful Lineage and AI-Assisted Documentation"](https://www.g2.com/survey_responses/atlan-review-12758713)**

**Rating:** 4.5/5.0 stars

_— Keith G._

[Read full review](https://www.g2.com/survey_responses/atlan-review-12758713)

### [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?

- **Ease of Use:** 8.4/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.9/10 (Category avg: 8.6/10)
- **Metadata Management :** 8.6/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.7/10 (Category avg: 8.7/10)

#### 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

### [Alation](https://www.g2.com/products/alation/reviews)

Alation is the creator of AIOS™, the open, governed, self-improving intelligence operating system for enterprises that cannot afford to get AI wrong. Having pioneered the data catalog market, Alation helps organizations establish trust in the agents, data, and context that power AI-driven decisions. The result is AI organizations can trust—enabling them to navigate regulatory complexity, maintain data fidelity, accelerate operational outcomes, and transform AI ambition into trusted business impact. Alation partners with the world’s leading to leverage better data to solve their most critical challenges.

**Average Rating:** 4.4/5.0

**Total Reviews:** 89

#### How Do G2 Users Rate Alation?

- **Ease of Use:** 8.3/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.7/10 (Category avg: 8.6/10)
- **Metadata Management :** 7.9/10 (Category avg: 8.4/10)
- **Data Lineage:** 7.2/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Alation?

- **Seller:** [Alation](https://www.g2.com/sellers/alation)
- **Company Website:** alation.com
- **Year Founded:** 2012
- **HQ Location:** Redwood City, CA
- **Twitter:** @Alation  
3,567 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=a7f7e9ccd16e7165128a966e9428e0691e7330918523a3dc7e2519043fe9a497&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3231829%2F&secure%5Burl_type%5D=linkedin_company_website)  
608 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 57% Large, 27% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Alation, allowing for efficient navigation and intuitive data discovery.
- Users value the **intuitive data discovery** capabilities of Alation, enhancing their ability to find and understand data.
- Users appreciate Alation's **intuitive navigation** , enhancing productivity and streamlining access to essential project documentation.
- Users value the **intuitive catalog structure** of Alation, enhancing data discovery and governance through effective collaboration.
- Users value Alation's **intuitive user interface** , simplifying navigation and enhancing productivity in data discovery and documentation.

##### Cons

- Users experience **slow performance** with Alation, particularly during search with larger datasets and metadata freshness issues.
- Users are frustrated by **missing features** like data quality tools and lack of visual indicators for hidden assets.
- Users note the **limited functionality** in Alation, especially regarding data quality and custom workflows.
- Users report **significant lineage limitations** in Alation, facing bugs and inconsistent support that complicate data tracking tasks.
- Users find the **user interface lacking** and suggest improvements for better organization and intuition in Alation.

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

**["Exceptional Tool and Team, Expanding Our Data Governance"](https://www.g2.com/survey_responses/alation-review-12007948)**

**Rating:** 5.0/5.0 stars

_— Eric N._

[Read full review](https://www.g2.com/survey_responses/alation-review-12007948)

**["A Solid Product With Areas for Refinement"](https://www.g2.com/survey_responses/alation-review-11980120)**

**Rating:** 5.0/5.0 stars

_— Melissa B._

[Read full review](https://www.g2.com/survey_responses/alation-review-11980120)

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

- [Is Alation a database?](https://www.g2.com/discussions/is-alation-a-database)
- [Which three are capabilities of Oracle Cloud Infrastructure data catalog service?](https://www.g2.com/discussions/which-three-are-capabilities-of-oracle-cloud-infrastructure-data-catalog-service) - 1 comment
- [Is Alation good?](https://www.g2.com/discussions/is-alation-good)
- [What does Alation software do?](https://www.g2.com/discussions/what-does-alation-software-do)

### [Google Cloud Data Catalog](https://www.g2.com/products/google-cloud-data-catalog/reviews)

A fully managed and highly scalable data discovery and metadata management service.

**Average Rating:** 4.4/5.0

**Total Reviews:** 25

#### How Do G2 Users Rate Google Cloud Data Catalog?

- **Ease of Use:** 8.7/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.5/10 (Category avg: 8.6/10)
- **Metadata Management :** 9.1/10 (Category avg: 8.4/10)
- **Data Lineage:** 7.8/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Google Cloud Data Catalog?

- **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?

- **Top Industries:** Computer Software
- **Company Size:** 46% Small, 29% Medium

#### What Are Recent G2 Reviews of Google Cloud Data Catalog?

**["Best centralised approach for GCP Projects"](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7589215)**

**Rating:** 4.5/5.0 stars

_— Nirav D._

[Read full review](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7589215)

**["The Google Cloud Data Catalog is a fantastic offering."](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7586462)**

**Rating:** 5.0/5.0 stars

_— Pranav R._

[Read full review](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7586462)

### [erwin Data Modeler](https://www.g2.com/products/quest-software-erwin-data-modeler/reviews)

Part of the Quest erwin Data Management Platform, delivering industry-leading enterprise data modeling. erwin Data Modeler provides the blueprints for trusted data. Integrated with erwin Data Intelligence, it connects models to governed metadata and business context - ensuring that what’s delivered in production matches the design, so data products are accurate, governed, and AI-ready.

**Average Rating:** 4.2/5.0

**Total Reviews:** 110

#### How Do G2 Users Rate erwin Data Modeler?

- **Ease of Use:** 8.4/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10)
- **Metadata Management :** 8.3/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.5/10 (Category avg: 8.7/10)

#### Who Is the Company Behind erwin Data Modeler?

- **Seller:** [Quest Software](https://www.g2.com/sellers/quest-software)
- **Company Website:** www.quest.com
- **Year Founded:** 1987
- **HQ Location:** Austin, TX
- **Twitter:** @Quest  
17,109 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ed19918b4e18facf79def69484660a2b3831e7c0b692c78c8af06464252d5f38&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2880%2F&secure%5Burl_type%5D=linkedin_company_website)  
3,569 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 40% Small, 37% Medium

#### What Do G2 Reviewers Say About erwin Data Modeler?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of erwin Data Modeler, simplifying data visualization and enhancing collaboration.
- Users value the **collaboration enhancements** of erwin Data Modeler, facilitating clearer communication between technical and business teams.
- Users appreciate the **clarity in designing and visualizing data models** , enhancing collaboration and reducing design errors.
- Users value the **effective data governance** capabilities of erwin Data Modeler, enhancing collaboration and clarity across teams.
- Users appreciate the **robust data management capabilities** of erwin Data Modeler for seamless integration and modeling.

##### Cons

- Users find the **licensing cost** of erwin Data Modeler to be prohibitively high, leading to shifts towards other tools.
- Users find the **complexity** of erwin Data Modeler challenging, particularly for new users or large models.
- Users find the **difficult interface** of erwin Data Modeler outdated and challenging, especially for newcomers.
- Users find **limited customization** options in erwin Data Modeler, which may hinder their ability to tailor the tool effectively.
- Users find erwin Data Modeler's interface to be **outdated** , making it challenging for new users to adapt effectively.

#### What Are Recent G2 Reviews of erwin Data Modeler?

**["Powerful Reverse Engineering for Keeping Logical and Physical Models in Sync"](https://www.g2.com/survey_responses/erwin-data-modeler-review-13149297)**

**Rating:** 4.0/5.0 stars

_— Brendan M._

[Read full review](https://www.g2.com/survey_responses/erwin-data-modeler-review-13149297)

**["Intuitive Data Modeling with Powerful Forward/Reverse Engineering"](https://www.g2.com/survey_responses/erwin-data-modeler-review-13077571)**

**Rating:** 4.0/5.0 stars

_— Prerak S._

[Read full review](https://www.g2.com/survey_responses/erwin-data-modeler-review-13077571)

#### What Are G2 Users Discussing About erwin Data Modeler?

- [How much does Erwin Data Modeler cost?](https://www.g2.com/discussions/how-much-does-erwin-data-modeler-cost)
- [What software is used for data Modelling?](https://www.g2.com/discussions/what-software-is-used-for-data-modelling)
- [What does a data modeler program do?](https://www.g2.com/discussions/what-does-a-data-modeler-program-do)
- [What is Erwin Data Modeler used for?](https://www.g2.com/discussions/what-is-erwin-data-modeler-used-for)

### [Appen](https://www.g2.com/products/appen/reviews)

Appen collects and labels images, text, speech, audio, video, and other data to create training data used to build and continuously improve the world’s most innovative artificial intelligence systems. We offer a state of the art, licensable data annotation platform to annotate training data use cases in computer vision and natural language processing. Our platform enhances accuracy and efficiency through our Smart Labeling and Pre-Labeling features which use Machine Learning to ease human annotations. You choose the level of service and security you want for data collection and annotation, from white-glove managed service to flexible self-service. Our expertise includes having a global crowd of over 1 million skilled contractors who speak over 235 languages and dialects, in over 70,000 locations and 170 countries, and the industry’s most advanced AI-assisted data annotation platform. Our reliable training data gives leaders in technology, automotive, financial services, retail, healthcare, and governments the confidence to deploy world-class AI products. Founded in 1996, Appen has customers and offices globally.

**Average Rating:** 4.2/5.0

**Total Reviews:** 33

#### How Do G2 Users Rate Appen?

- **Ease of Use:** 8.2/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.2/10 (Category avg: 8.6/10)
- **Metadata Management :** 8.0/10 (Category avg: 8.4/10)
- **Data Lineage:** 7.8/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Appen?

- **Seller:** [Appen](https://www.g2.com/sellers/appen)
- **Year Founded:** 1996
- **HQ Location:** Kirkland, Washington, United States
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b0931c0a7f2c53197a2b59e80de4a7fdfa27c61180c1a3b6c615dca728909c73&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fappen&secure%5Burl_type%5D=linkedin_company_website)  
20,647 employees on LinkedIn®
- **Ownership:** ASX:APX
- **Total Revenue (USD mm):** $244,900

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services
- **Company Size:** 54% Small, 26% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **flexibility** of Appen, enabling them to engage in diverse and interesting projects from their cell phones.
- Users appreciate the **ease of use** of Appen, enabling task completion effortlessly through their cell phones.
- Users appreciate the **flexibility** of Appen, enabling engaging and diverse projects that enhance their work experience.

##### Cons

- Users experience frequent **work interruptions** , facing challenges like inconsistent availability and lengthy qualification processes.
- Users experience **low compensation** due to inconsistent work availability and monthly payments, affecting income stability.
- Users find the **navigation confusing** and experience frequent disconnects, leading to frustration while using Appen.
- Users often face **connectivity issues** , experiencing confusion while navigating and frequent disconnections from the app.
- Users find the **navigation confusing** , often resulting in unexpected logouts that disrupt their experience with Appen.

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

**["Ideal for Freelancers, Simplicity with Room for Support Improvement"](https://www.g2.com/survey_responses/appen-review-12550258)**

**Rating:** 5.0/5.0 stars

_— Ashish S._

[Read full review](https://www.g2.com/survey_responses/appen-review-12550258)

**["Robust Crowdsourcing Platform for AI and Language Tasks"](https://www.g2.com/survey_responses/appen-review-12769449)**

**Rating:** 4.0/5.0 stars

_— Sina A._

[Read full review](https://www.g2.com/survey_responses/appen-review-12769449)

### [Collibra](https://www.g2.com/products/collibra/reviews)

Try Collibra for free @ Collibra.com/tour Collibra is for organizations with complex data challenges, hybrid data ecosystems—and big ambitions for data and AI. We help organizations who are trying to accelerate data and AI use cases while ensuring compliance, but are struggling with fragmented governance and visibility across the whole hybrid data ecosystem. Collibra unifies governance for data and AI across every system, data source and user—to create safe autonomy and a foundation for scaling AI and data use cases. With Collibra, you can accelerate all your data and AI use cases, safely and with well–understood data. That’s Data Confidence.

**Average Rating:** 4.2/5.0

**Total Reviews:** 99

#### How Do G2 Users Rate Collibra?

- **Ease of Use:** 8.0/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10)
- **Metadata Management :** 8.0/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.0/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Collibra?

- **Seller:** [Collibra](https://www.g2.com/sellers/collibra)
- **Company Website:** www.collibra.com
- **Year Founded:** 2008
- **HQ Location:** New York, New York
- **Twitter:** @collibra  
5,756 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fcd053a42a3c664461e0d84dcd30ce00a076bf85f5efcb48a6ef76db774cc0d1&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F288365%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,095 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Financial Services, Banking
- **Company Size:** 72% Large, 19% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users love the **unified data intelligence platform** of Collibra, enhancing collaboration and visibility for CDO teams.
- Users value the **comprehensive data management** capabilities of Collibra, enhancing compliance and fostering alignment across teams.
- Users value the **collaboration capabilities** of Collibra, enhancing alignment between Business and IT across the platform.
- Users find Collibra to be **intuitive and easily configurable** , enhancing their data management and governance experience.
- Users value the **seamless integrations** with diverse tools, enhancing data ecosystems and streamlining governance processes.

##### Cons

- Users face **complexity issues** with Collibra, leading to frustrations in onboarding and configuration as well as bottlenecks.
- Users struggle with **limited functionality** due to complex navigation and unintuitive language, hindering effective use of Collibra.
- Users find **Collibra complex** , with challenges in onboarding, unclear roles, excessive notifications, and technical issues hindering efficiency.
- Users face **integration issues** with Collibra, leading to bottlenecks and inconsistent connections with other tools.
- Users struggle with **user interface issues** in Collibra, facing navigation challenges and unclear language hindering usability.

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

**["Powerful Data Governance and Quality Platform"](https://www.g2.com/survey_responses/collibra-review-12128662)**

**Rating:** 5.0/5.0 stars

_— Katerina V._

[Read full review](https://www.g2.com/survey_responses/collibra-review-12128662)

**["Collibra Data Quality Module"](https://www.g2.com/survey_responses/collibra-review-7563210)**

**Rating:** 5.0/5.0 stars

_— Frank L._

[Read full review](https://www.g2.com/survey_responses/collibra-review-7563210)

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

- [What is Collibra data governance tool?](https://www.g2.com/discussions/what-is-collibra-data-governance-tool)
- [Is Collibra a good tool?](https://www.g2.com/discussions/is-collibra-a-good-tool)
- [What can Collibra do?](https://www.g2.com/discussions/what-can-collibra-do)
- [What are the features of Collibra?](https://www.g2.com/discussions/what-are-the-features-of-collibra)

### [Cloudera](https://www.g2.com/products/cloudera/reviews)

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments.

**Average Rating:** 4.1/5.0

**Total Reviews:** 131

#### How Do G2 Users Rate Cloudera?

- **Ease of Use:** 8.3/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.9/10 (Category avg: 8.6/10)
- **Metadata Management :** 9.1/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.8/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Cloudera?

- **Seller:** [Cloudera](https://www.g2.com/sellers/cloudera)
- **Company Website:** www.cloudera.com
- **Year Founded:** 2008
- **HQ Location:** Santa Clara, CA
- **Twitter:** @cloudera  
106,442 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=4b6b5c58818dc39001f93594864d8d88fc876550d3da9306b76f69639a789f14&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F229433%2F&secure%5Burl_type%5D=linkedin_company_website)  
3,446 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Software Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 42% Large, 32% Small

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **brilliant and easy-to-use interface** of Cloudera, enhancing their data analysis experience.
- Users value the **seamless scalability** of Cloudera, effectively handling vast amounts of data with ease.
- Users appreciate the **strong security features** of Cloudera, ensuring reliable data management and protection.
- Users value Cloudera for its **comprehensive big data management tools** , enhancing their data handling and scalability experience.
- Users appreciate the **scalability and ease of use** of Cloudera, making data management and reporting effortless.

##### Cons

- Users note that Cloudera's platform can be **expensive** to maintain and challenging to set up, especially for beginners.
- Users find the **complexity** of Cloudera challenging, especially when managing SQL queries and customization.
- Users find the **learning curve steep** with Cloudera, making setup and navigation challenging for beginners.
- Users find Cloudera's **poor documentation** makes navigating complex data configurations challenging and complicates error resolution.
- Users face significant **access issues** with Cloudera, including authorization errors and limited documentation support.

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

**["Reliable Platform for Managing Large-Scale Data Pipelines"](https://www.g2.com/survey_responses/cloudera-review-11455117)**

**Rating:** 4.5/5.0 stars

_— Paritosh C._

[Read full review](https://www.g2.com/survey_responses/cloudera-review-11455117)

**["Easy to Use, Reliable, and Great for Team Collaboration"](https://www.g2.com/survey_responses/cloudera-review-12695378)**

**Rating:** 4.0/5.0 stars

_— Verified User in Computer Software_

[Read full review](https://www.g2.com/survey_responses/cloudera-review-12695378)

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

- [What is Cloudera used for?](https://www.g2.com/discussions/what-is-cloudera-used-for) - 1 comment
- [What is Hortonworks Data Platform used for?](https://www.g2.com/discussions/what-is-hortonworks-data-platform-used-for)
- [What is Cloudera Data Flow used for?](https://www.g2.com/discussions/what-is-cloudera-data-flow-used-for)
- [What is Cloudera Navigator used for?](https://www.g2.com/discussions/what-is-cloudera-navigator-used-for)
- [What is Cloudera Data Engineering used for?](https://www.g2.com/discussions/what-is-cloudera-data-engineering-used-for)

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

Decube is a Context Layer platform specifically designed for the AI era, providing organizations with the ability to give their data meaning, memory, and trust. This innovative system integrates various components such as metadata management, automated lineage tracking, data quality assurance, and observability to create a comprehensive real-time map of data dynamics. By understanding how data operates, flows, and its reliability, Decube empowers enterprises to make informed decisions and effectively manage AI workloads. Targeted primarily at enterprises that rely heavily on data-driven decision-making, Decube addresses a critical challenge faced by many organizations: the lack of contextual understanding of their data. In an age where data is abundant, the real issue lies in the ability to interpret and utilize that data effectively. Decube provides a connected understanding of the entire data ecosystem, which helps eliminate blind spots and enhances governance. This contextual awareness is essential for organizations looking to leverage AI technologies and ensure that their models, dashboards, and agents operate with greater intelligence and safety. Key features of Decube include its robust metadata management capabilities, which allow users to track and manage data lineage effortlessly. This feature ensures that organizations can trace the origins and transformations of their data, thereby enhancing transparency and accountability. Additionally, Decube’s focus on data quality means that users can trust the information they are working with, reducing the risk of errors in critical decision-making processes. The observability aspect of the platform further enables organizations to monitor data flows in real-time, ensuring that any issues can be identified and addressed promptly. The benefits of using Decube extend beyond mere data management. By providing a living, interconnected understanding of data, Decube enhances the overall operational confidence of organizations. This platform not only strengthens governance but also facilitates smarter decision-making by ensuring that all data-driven models are built on a foundation of reliable and contextualized information. As businesses increasingly depend on trustworthy data and AI-ready infrastructure, Decube stands out as a vital tool that equips them with the necessary context to navigate the complexities of the modern data landscape.

**Average Rating:** 4.6/5.0

**Total Reviews:** 23

#### How Do G2 Users Rate decube?

- **Ease of Use:** 9.4/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 9.6/10 (Category avg: 8.6/10)
- **Metadata Management :** 9.6/10 (Category avg: 8.4/10)
- **Data Lineage:** 9.6/10 (Category avg: 8.7/10)

#### Who Is the Company Behind decube?

- **Seller:** [Decube Data](https://www.g2.com/sellers/decube-data)
- **Company Website:** decube.io
- **Year Founded:** 2022
- **HQ Location:** Kuala Lumpur
- **Twitter:** @decube\_data  
113 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=61c6c620c5b0ad99fb778aafdcb0a070031cb73ca380f3342b3b61feada3041f&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdecube-data%2F&secure%5Burl_type%5D=linkedin_company_website)  
44 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services
- **Company Size:** 39% Medium, 35% Small

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

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **intuitive user interface** of Decube, which simplifies data monitoring and enhances overall efficiency.
- Users find Decube's **ease of use** remarkable, thanks to its intuitive UI and seamless data integration features.
- Users appreciate the **real visibility into data pipelines** provided by Decube, enhancing early issue detection and understanding.
- Users appreciate the **real-time visibility and proactive monitoring** of data quality offered by Decube, enhancing data management.
- Users love the **easy data monitoring and clear insights** provided by Decube's intuitive interface and dashboard.

##### Cons

- Users find the **limited functionality** of decube frustrating, especially lacking bulk testing and advanced data insights.
- Users find the **complex setup** of Decube challenging, requiring time and effort to configure effectively.
- Users find **limited features** in Decube, requiring extra effort to access deeper data insights and configurations.
- Users find the **missing features** of Decube, like API monitoring and group-by options, limit its effectiveness.
- Users often face challenges due to **poor customer support** , making it difficult to get timely assistance when needed.

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

**["Effortless Data Quality and Trust with Decube"](https://www.g2.com/survey_responses/decube-review-11920093)**

**Rating:** 4.5/5.0 stars

_— Ahsan Y._

[Read full review](https://www.g2.com/survey_responses/decube-review-11920093)

**["Comprehensive Data Trust Platform with Powerful Features, but Support Needs Improvement"](https://www.g2.com/survey_responses/decube-review-11833181)**

**Rating:** 5.0/5.0 stars

_— Sivani V._

[Read full review](https://www.g2.com/survey_responses/decube-review-11833181)

### [Select Star](https://www.g2.com/products/select-star/reviews)

Select Star is a modern data governance platform that helps organizations manage and understand their data at scale, enabling AI, analytics, and self-service across the business. It automatically catalogs datasets, traces end-to-end lineage, and builds a shared business glossary and semantic layer, so teams can confidently work with trusted data. With a user-friendly data portal and built-in automation, Select Star supports use cases including data democratization, data governance, semantic layers, and cloud data migrations serving as a foundational layer for enterprise AI and data initiatives.

**Average Rating:** 4.5/5.0

**Total Reviews:** 55

#### How Do G2 Users Rate Select Star?

- **Ease of Use:** 8.9/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.2/10 (Category avg: 8.6/10)
- **Metadata Management :** 8.7/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.9/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Select Star?

- **Seller:** [Select Star](https://www.g2.com/sellers/select-star)
- **Year Founded:** 2020
- **HQ Location:** San Francisco, CA
- **Twitter:** @selectstarhq  
389 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=50f3d04e78469fdf3907cd995a11aa9452d5bf67d28b688ef6d0888bf6225b34&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fselectstarhq%2F&secure%5Burl_type%5D=linkedin_company_website)  
17 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Real Estate
- **Company Size:** 51% Medium, 38% Large

#### What Do G2 Reviewers Say About Select Star?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Select Star, finding it simple and efficient for daily data management tasks.
- Users value the **robust data lineage feature** in Select Star, which simplifies data navigation and understanding.
- Users value the **clean and intuitive user interface** of Select Star, enhancing usability and simplifying complex data tasks.
- Users value the **easy data discovery** capabilities of Select Star, simplifying navigation within complex data architectures.
- Users appreciate the **ease of locating data fields** with Select Star, enhancing data discovery and collaboration.

##### Cons

- Users feel the **limited functionality** of Select Star hinders the accessibility of insights and robust reporting capabilities.
- Users find **lineage limitations** in Select Star, making it difficult to visualize and filter dependencies effectively.
- Users find the **complex setup** for a dbt mesh ecosystem challenging, requiring significant effort for project unification.
- Users find the **difficult learning curve** of Select Star makes it challenging to gain quick value from the product.
- Users feel the need for **more straightforward guidance** with Select Star to maximize value without extensive expertise.

#### What Are Recent G2 Reviews of Select Star?

**["Seamless Integration, Solid Support"](https://www.g2.com/survey_responses/select-star-review-11904733)**

**Rating:** 5.0/5.0 stars

_— Steve K._

[Read full review](https://www.g2.com/survey_responses/select-star-review-11904733)

**["Intuitive Data Discovery Made Effortless"](https://www.g2.com/survey_responses/select-star-review-11919348)**

**Rating:** 5.0/5.0 stars

_— Clara C._

[Read full review](https://www.g2.com/survey_responses/select-star-review-11919348)

### [Secoda](https://www.g2.com/products/secoda/reviews)

Secoda is an AI-powered data governance platform designed to help organizations explore, understand, and utilize their data effectively. By providing a comprehensive platform that connects to 75+ data sources, pipelines, warehouses, and visualization tools, Secoda aims to create a unified source of truth for businesses. This functionality is particularly valuable for organizations looking to enhance their self-serve analytics, streamline operations, and improve decision-making. Targeted at data teams, business stakeholders, and organizations of all sizes, Secoda serves as an essential tool for those who need to manage and interpret large volumes of data. Its user-friendly interface ensures that individuals with varying levels of technical expertise can leverage the platform to gain actionable insights. Companies such as Vanta, Cardinal Health, ID.me, and Dialpad have adopted Secoda to monitor the health of their data ecosystems, enhance the efficiency of their data teams, and scale AI readiness. One of Secoda’s core advantages is its ability to unify data cataloging, enterprise governance, and observability into a single, streamlined platform. This consolidation not only reduces the overhead of managing multiple tools but also powers Secoda AI with rich, connected context, enabling teams to focus on insights instead of infrastructure. Secoda automates key data management tasks including documentation, tagging, glossary term creation, and policy creation. This automation enables users to quickly discover and access relevant data and insights without extensive manual effort. By streamlining these processes, Secoda not only saves valuable time but also empowers teams to make confident, data-driven decisions based on current, well-organized information, ultimately driving better business outcomes. Overall, Secoda stands out in the data management landscape by offering a comprehensive, AI-driven solution that caters to the needs of both technical and non-technical users. Its ability to create a single source of truth, coupled with its integration of multiple functionalities into one platform, positions it as a valuable asset for organizations aiming to harness the full potential of their data.

**Average Rating:** 4.5/5.0

**Total Reviews:** 55

#### How Do G2 Users Rate Secoda?

- **Ease of Use:** 8.2/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 9.3/10 (Category avg: 8.6/10)
- **Metadata Management :** 9.5/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.9/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Secoda?

- **Seller:** [Secoda](https://www.g2.com/sellers/secoda)
- **Year Founded:** 2021
- **HQ Location:** Toronto, CA
- **Twitter:** @SecodaHQ  
923 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8f1837632c4ab80c8e59891b62d653832890bc68b79a494f0d793f7a5eb73e02&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsecodahq%2Fabout&secure%5Burl_type%5D=linkedin_company_website)  
19 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Computer Software, Financial Services
- **Company Size:** 65% Medium, 18% Small

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

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **data lineage** feature of Secoda for enhancing metadata integration and facilitating easy discovery across teams.
- Users appreciate the **self-serve onboarding** of Secoda, making it easy to empower teams with data governance.
- Users value the **integration capabilities** of Secoda, seamlessly connecting to platforms like Looker Studio and Salesforce.
- Users appreciate the **ease of use** of Secoda, making it accessible for both tech and non-tech users.
- Users find the **data management features** in Secoda invaluable for knowledge sharing and simplifying data understanding.

##### Cons

- Users find the **learning difficulty** with Secoda's settings and integrations frustrating, particularly for nontechnical team members.
- Users note the **product immaturity** of Secoda, with bugs and missing features as challenges to their experience.
- Users highlight the need for significant **improvement** in functionality and usability to derive real value from Secoda.
- Users note the **limited functionality** of Secoda, stating it lacks essential features and struggles with usability.
- Users experience **performance issues** with Secoda, facing syncing problems and minor bugs that hinder usability.

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

**["Making real progress with metadata, lineage, documentation and AI use cases"](https://www.g2.com/survey_responses/secoda-review-11392959)**

**Rating:** 4.5/5.0 stars

_— Verified User in Financial Services_

[Read full review](https://www.g2.com/survey_responses/secoda-review-11392959)

**["Secoda offers great integration with Snowflake, dbt, Tableau for Data Cataloging and AI assistance"](https://www.g2.com/survey_responses/secoda-review-11049626)**

**Rating:** 5.0/5.0 stars

_— Surya Kant M._

[Read full review](https://www.g2.com/survey_responses/secoda-review-11049626)

### [Coalesce Catalog (formerly CastorDoc)](https://www.g2.com/products/castor-doc/reviews)

Coalesce Catalog is a collaborative, automated data discovery & catalog tool. We believe that data people spend way too much time trying to find and understand their data. Coalesce Catalog redesigns how data people collaborate. It provides a single source of truth to reference and document all the knowledge related to data within your company. If you are looking for a table related to your customers, just look for it as you would in Google, and Coalesce Catalog provides you with all the context you will need for your analysis. Inspired by internal tools developed by Uber, Airbnb, Lyft, and Spotify, Coalesce Catalog has developed a plug-and-play solution that deploys in minutes to drive value for companies of all sizes. Discover and catalog your data today with Coalesce Catalog.

**Average Rating:** 4.7/5.0

**Total Reviews:** 63

#### How Do G2 Users Rate Coalesce Catalog (formerly CastorDoc)?

- **Ease of Use:** 9.6/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 9.9/10 (Category avg: 8.6/10)
- **Metadata Management :** 9.9/10 (Category avg: 8.4/10)
- **Data Lineage:** 9.9/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Coalesce Catalog (formerly CastorDoc)?

- **Seller:** [Coalesce](https://www.g2.com/sellers/coalesce)
- **Company Website:** coalesce.io
- **Year Founded:** 2020
- **HQ Location:** San Francisco, CA
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8cad3d021ee68b3fe6029419b441f3415268c9bec4a8ae062757ce5b35d316cd&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fcoalesceio%2F&secure%5Burl_type%5D=linkedin_company_website)  
118 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 59% Medium, 27% Large

#### What Do G2 Reviewers Say About Coalesce Catalog (formerly CastorDoc)?

_AI-generated summary from verified user reviews_

##### Pros

- Users commend the **ease of use** of Coalesce Catalog, finding it intuitive and powerful for data governance.
- Users appreciate the **easy collaboration** features of Coalesce Catalog, enhancing teamwork and knowledge sharing effectively.
- Users appreciate the **seamless connectivity** of Coalesce Catalog, simplifying data access and integration across multiple sources.
- Users appreciate the **data lineage feature** for simplifying data discovery and enhancing connectivity across sources.
- Users appreciate the **intuitive interface** of Coalesce Catalog, enhancing data governance and simplifying data discovery.

##### Cons

- Users find the **connector issues** limiting, as direct AI agent integration with the Catalog knowledge is unavailable.
- Users face **integration issues** preventing connection of other AI agents to Coalesce Catalog, limiting functionality and flexibility.
- Users face a **limitation in AI connectivity** , as integrating other AI agents with the Catalog knowledge remains unavailable.

#### What Are Recent G2 Reviews of Coalesce Catalog (formerly CastorDoc)?

**["User-friendly & easy adoption for all of our data users"](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-11753164)**

**Rating:** 4.5/5.0 stars

_— Théo C._

[Read full review](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-11753164)

**["A great tool to organize and explain your data hub"](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-10622007)**

**Rating:** 4.5/5.0 stars

_— Verified User in Computer Software_

[Read full review](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-10622007)

### [IBM InfoSphere Information Governance Catalog](https://www.g2.com/products/ibm-infosphere-information-governance-catalog/reviews)

IBM® Information Governance Catalog is an interactive, web-based tool that allows users to explore, understand and analyze information. Users can create, manage and share a common business language, document and enact policies and rules and track the usage and consumption of data within a lineage report providing trusted information for compliance and insights. Learn More: https://ibm.co/2xmfLsK

**Average Rating:** 4.0/5.0

**Total Reviews:** 16

#### How Do G2 Users Rate IBM InfoSphere Information Governance Catalog?

- **Ease of Use:** 7.6/10 (Category avg: 8.6/10)

#### Who Is the Company Behind IBM InfoSphere Information Governance Catalog?

- **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?

- **Company Size:** 53% Large, 26% Medium

#### What Are Recent G2 Reviews of IBM InfoSphere Information Governance Catalog?

**["Searching for assets inside Information Governance Catalog is easy"](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-4368588)**

**Rating:** 4.5/5.0 stars

_— Gyuzel Z._

[Read full review](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-4368588)

**["Using IGC to build our Business Metadata Glossary"](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-1744120)**

**Rating:** 5.0/5.0 stars

_— Verified User in Banking_

[Read full review](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-1744120)

### [data.world](https://www.g2.com/products/data-world/reviews)

data.world is the most-adopted data catalog and governance platform on the market. Built on a unique knowledge graph foundation, data.world seamlessly integrates with your existing systems. We set the standard for swift, people-centric governance. We don't just manage data; we unlock its potential, paving the way for responsible AI adoption and data-driven decision-making at scale. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500.

**Average Rating:** 4.2/5.0

**Total Reviews:** 12

#### How Do G2 Users Rate data.world?

- **Ease of Use:** 8.8/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 9.2/10 (Category avg: 8.6/10)
- **Metadata Management :** 8.8/10 (Category avg: 8.4/10)
- **Data Lineage:** 9.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind data.world?

- **Seller:** [data.world](https://www.g2.com/sellers/data-world)
- **Year Founded:** 2016
- **HQ Location:** Austin, Texas
- **Twitter:** @datadotworld  
5,498 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=d19982232df68ef1af170e44e37c5437a701e25d9bb373912f55a29c911c86f7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdata.world%2F&secure%5Burl_type%5D=linkedin_company_website)  
100 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 67% Small, 25% Medium

#### What Do G2 Reviewers Say About data.world?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use in data analytics** , making data discovery enjoyable and accessible.
- Users find the **data discovery and analytics** features of data.world to be user-friendly and effective.
- Users love the **ease of use** for discovering data and performing analytics with data.world.
- Users value the **ease of use in data analytics** , enhancing their ability to discover insights from data.
- Users find the **ease of use** in data.world enhances their experience in discovering and analyzing data effectively.

##### Cons

- Users report experiencing **poor customer support** , making it difficult to resolve issues when they arise.
- Users experience **poor support services** with data.world, leading to difficulties in resolving issues and queries.

#### What Are Recent G2 Reviews of data.world?

**["One of the most mind-blowing venture information index"](https://www.g2.com/survey_responses/data-world-review-8236137)**

**Rating:** 5.0/5.0 stars

_— Rahul V._

[Read full review](https://www.g2.com/survey_responses/data-world-review-8236137)

**["Very attractive and informative"](https://www.g2.com/survey_responses/data-world-review-9974366)**

**Rating:** 4.5/5.0 stars

_— AASIM I._

[Read full review](https://www.g2.com/survey_responses/data-world-review-9974366)

#### What Are G2 Users Discussing About data.world?

- [What is data.world used for?](https://www.g2.com/discussions/what-is-data-world-used-for) - 1 comment

### [IBM watsonx.data intelligence](https://www.g2.com/products/ibm-watsonx-data-intelligence/reviews)

IBM watsonx.data intelligence revolutionizes the way organizations curate, manage, and utilize data by leveraging the power of AI to simplify data delivery across hybrid ecosystems. IBM watsonx.data intelligence is a comprehensive solution that integrates capabilities such as data governance (formerly IBM Knowledge Catalog), data lineage (formerly IBM Manta Data Lineage), data sharing, and data quality management. It empowers organizations to discover, trust, and access meaningful data, providing consumers with reliable data products. Explore Demo Library - https://www.ibm.com/products/watsonx-data-intelligence/demo-library Start your free trial - https://dataplatform.cloud.ibm.com/registration/stepone?context=df&apps=all&uucid=1227cc9e37cb9292&preselect\_region=true

**Average Rating:** 4.2/5.0

**Total Reviews:** 24

#### How Do G2 Users Rate IBM watsonx.data intelligence?

- **Ease of Use:** 8.4/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 7.5/10 (Category avg: 8.6/10)
- **Metadata Management :** 7.5/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind IBM watsonx.data intelligence?

- **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?

- **Company Size:** 38% Small, 34% Large

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **automation features** of IBM watsonx.data intelligence, simplifying data flow understanding and reducing manual efforts.
- Users value the **automated data lineage visualization** of IBM watsonx.data intelligence for improved understanding and governance of data flows.
- Users value the **data lineage capabilities** of IBM Watsonx.data intelligence, enhancing data governance and visualization across systems.
- Users appreciate the **ease of use** of IBM Manta Data Lineage, enhancing understanding and governance of data flows.
- Users value the **efficiency** of IBM watsonx.data intelligence, streamlining data management and enhancing governance processes significantly.

##### Cons

- Users face **complex implementation** challenges due to intricate setups and integration issues, requiring specialized expertise.
- Users experience **setup complexity** with IBM watsonx.data intelligence, requiring specialized expertise and potentially high costs for implementation.
- Users find the **implementation cost to be high** , making it potentially out of reach for many organizations.
- Users find that **specialized expertise is required** for proper implementation of IBM watsonx.data intelligence, complicating the setup process.
- Users find the **extra costs** associated with IBM watsonx.data intelligence to be a significant barrier to access.

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

**["Intuitive Data Lineage Solution"](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10653356)**

**Rating:** 4.5/5.0 stars

_— srikanth c._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10653356)

**["Good Data Management Tool !"](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10711565)**

**Rating:** 4.0/5.0 stars

_— Rahul C._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10711565)

- ‹ Prev‹ Prev
- 1
- [2](/categories/machine-learning-data-catalog?order=g2_score&page=2#product-list)
- [3](/categories/machine-learning-data-catalog?order=g2_score&page=3#product-list)
- [4](/categories/machine-learning-data-catalog?order=g2_score&page=4#product-list)
- [5](/categories/machine-learning-data-catalog?order=g2_score&page=5#product-list)
- [6](/categories/machine-learning-data-catalog?order=g2_score&page=6#product-list)
- [Next ›Next ›](/categories/machine-learning-data-catalog?order=g2_score&page=2#product-list)

Spotlight Categories

[Loyalty Management Software](https://www.g2.com/categories/loyalty-management)

[Product Information Management (PIM) Systems](https://www.g2.com/categories/product-information-management-pim)

[Inbound Call Tracking Software](https://www.g2.com/categories/inbound-call-tracking)

[Robotic Process Automation (RPA) Software](https://www.g2.com/categories/robotic-process-automation-rpa)

[Travel Management Solutions](https://www.g2.com/categories/travel-management)

Similar Categories

- [Infrastructure as a Service (IaaS)](/categories/infrastructure-as-a-service-iaas)
- [Active Metadata Management](/categories/active-metadata-management)
- [Address Verification](/categories/address-verification)
- [AIOps Platforms](/categories/aiops-platforms)
- [Application Server](/categories/application-server)

- [Blockchain](/categories/blockchain)
- [Cloud File Storage](/categories/cloud-file-storage)
- [Database Software](/categories/database-software)
- [Data Center Infrastructure Management (DCIM)](/categories/data-center-infrastructure-management-dcim)
- [Data Center Networking](/categories/data-center-networking)

- [Data Exchange Platforms](/categories/data-exchange-platforms)
- [Data Fabric](/categories/data-fabric)
- [Data Integration Tools](/categories/data-integration-tools)
- [Data Management Software](/categories/data-management-software)
- [Data Mapping](/categories/data-mapping)

[Browse Machine Learning Data Catalog Themes](/categories/machine-learning-data-catalog/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 October 3, 2024

Machine learning data catalogs allow companies to categorize, access, interpret, and collaborate around company data across multiple data sources, while maintaining a high level of governance and access management. Artificial intelligence is key to many features of machine learning data catalogs, enabling functionality such as machine learning recommendations, natural language querying, and dynamic data masking for enhanced security purposes.

Companies can utilize machine learning data catalogs to maintain data sets in a single location so that searching for and discovering data is simple for everyday business users and analysts alike. Users have the ability to comment on, share, and recommend data sets so colleagues can have an immediate understanding of what they are querying. Additionally, IT administrators can put into place user provisioning to ensure unauthorized employees are not accessing sensitive data.

Machine learning data catalogs are most frequently implemented by companies that have multiple data sources, are searching for one source of truth, and are attempting to scale data usage company-wide. These products are generally administered by IT departments, who can maintain organization and security, but data can be accessed by data scientists or analysts and the average business user. The data can then be transformed, modeled, and visualized either directly in the machine learning data catalog or through an integration with [business intelligence software](https://www.g2.com/categories/business-intelligence).

It should be noted that not all machine learning data catalogs provide data preparation capabilities and may require an integration with a [business intelligence platform](https://www.g2.com/categories/business-intelligence-platforms). Additionally, these tools differ from [master data management software](https://www.g2.com/categories/master-data-management-mdm) due to their enhanced governance, collaboration, and machine learning functionality.

To qualify for inclusion in the Machine Learning Data Catalog category, a product must:

- Organize and consolidate data from all company sources in a single repository
- Provide user access management for security and data governance purposes
- Allow business users to search and access the data from within the catalog
- Offer collaboration features around data sets, including categorizing, commenting, and sharing
- Give intelligent recommendations based on machine learning for quicker access to relevant data 

Show More

* * *

## How Do You Choose the Right Machine Learning Data Catalog Software?

### What You Should Know About Healthcare Claims Management Software

### What is a Machine Learning Data Catalog?

Machine learning data catalog (MLDC) is an automated data catalog that carries out tasks like crawling metadata, cataloging, and classifying personally identifiable information (PII) data. Machine learning data catalogs organize the dataset inventory using metadata.

Data catalogs help companies know where the data is stored, thus reducing the time taken to identify data and making it easily accessible for analytics. They are inventories of assets like tables, schema, files, and charts in organizations, aiding in solving a company's data discovery, quality, and governance challenges.

### What does MLDC Stand For?

MLDC is an acronym for Machine Learning Data Catalog. 

### What are the Common Features of Machine Learning Data Catalogs?

Machine learning data catalogs simplify the manual functions of a data catalog. A data catalog is an essential part of the data management strategy of any organization. Some of the features of machine learning data catalogs are:

**Data ingestion and discovery:** Machine learning data catalogs must have prebuilt adapters to connect to different company systems like applications, databases, files, and external APIs. These adapters help in discovering metadata from systems. Metadata can be table names, attribute names, and constraints. The feature helps build native connectivity like integrations for data sources, business intelligence (BI) solutions, and data science tools.

**Business glossary:** Although a good amount of data is stored in the repository, it is also essential for the users to understand what the stored data means. The glossary feature links this data to business terms giving it more meaning. 

**Automated data labeling:** Data labeling is a prerequisite for machine learning algorithms. Automated data labeling is more accurate than manual since it eliminates human errors. Data labeling usually involves annotators identifying objects in images to build quality artificial intelligence (AI) training data. Automated labeling eliminates the challenges posed by the tedious annotation cycles.

**Data lineage:** Data lineage is the process that helps the users know who, why, when, and where changes are made to the data. It is a part of metadata management. MLDCs automate the data lineage process. Data lineage helps determine when new or changed data require retraining machine learning models. MLDCs usually parse through query logs into data lakes and other data sources automatically to create a data lineage map.

**Data quality monitoring and anomaly detection:** Data quality monitoring helps users understand if the data came from a trusted source. The machine learning data catalog also has a feature to identify sudden changes in data using machine learning algorithms. The users are immediately alerted to any changes or anomalies that are detected. 

**Semantic search for data sets:** Machine learning data catalogs provide users with visual and intuitive searches like search engines. Almost every user in any organization is a data user, but not everyone can use SQL queries to use data. The semantic search feature makes it easier for all users to discover data sets.

**Compliance capabilities:** This feature ensures that sensitive data is not exposed and that the user can trust the data. It further helps keep data governance policies in place and strengthen data management in the organization. Data stewards can identify low-quality data and restrict access to sensitive data, thus helping comply with regulations such as the General Data Protection Regulation (GDPR).

**Data profiling:** Data profiling helps check the data from the data source and collects information about it. This process helps in knowing data quality issues much better, thus making the data management process more efficient.

### What are the Benefits of Machine Learning Data Catalogs?

A machine learning data catalog provides several benefits to different types of users in the organization. These include:

**Ease in data curation:** Data curation is a process of collecting, organizing, labeling, and cleaning data. Machine learning data catalogs validate metadata and organize insights into correct repositories using machine learning algorithms.

**Ease of search:** Because of semantic search, it becomes easier for non-technical users to search and discover data for use since they do not have to use SQL queries every time to access data.

**Ease in data collaboration:** Machine learning data catalogs help the users collaborate, use, and share data sets because machine learning data catalogs ease finding and storing siloed data.

### Who Uses Machine Learning Data Catalogs?

Machine learning data catalogs centralize metadata for various data assets. By organizing the metadata, MLDCs help organizations to govern data access.

**Data analysts:** Data analysts use MLDC to discover, classify, and manipulate data for their analytics processes. They can also discover AI or machine learning models, understand how they work, and import them into their BI tools. Data catalogs help data analysts make companies into self-service organizations. Self-service analytics is important for any organization that wants to be driven by insights. Machine learning data catalogs help the users know the means to find, understand, and trust data.

**Marketers:** Marketing teams use the machine learning data catalog more commercially. They obtain insights for making better decisions using data catalogs.

**Data scientists:** Data scientists usually publish their models for reuse. Data scientists always look for one platform that centralizes data for different projects. 

### Challenges with Machine Learning Data Catalogs

Although machine learning data catalogs help solve major challenges in traditional data catalogs like data discovery and data lineage, MLDCs also come with challenges.  

**Scalability:** It is tricky for all MLDCs to support a huge metadata volume. Sometimes, the data catalogs break down due to performance issues when overloaded with enormous amounts of metadata. Initially, data used to be stored in the company's mainframe data center. However, due to today's big data, machine learning data catalogs must keep track of data in both cloud and data lakes.

**Fragmentation in evaluating a product:** If a data catalog is too bulky, it causes fragmentation in the user's journey of evaluating a product. Too much data makes users use too many tools, thus breaking a seamless experience into fragments.

### How to Buy Machine Learning Data Catalogs

#### Requirements Gathering (RFI/RFP) for Machine Learning Data Catalogs

The machine learning data catalog offers many features to help users identify usable data. A buyer can choose the right MLDC software depending on the organization's needs. RFP/RFIs help the organization look for pricing, product features, and guidelines.

#### Compare Machine Learning Data Catalog Products

**Create a long list**

The first step is to look for all the possible players in the space. This gives an advantage of evaluating the vendors for the price, product features, and customer service. 

**Create a short list**

After evaluating the potential vendors, the company can narrow the list to those who check all their boxes.

**Conduct demos**

Demos help in understanding the product as a whole. A team of IT professionals and data scientists should join these demos to understand the product's functionality, whereas the marketing team can join in to analyze the business use of the software in the projects.

#### Selection of Machine Learning Data Catalogs

**Choose a selection team**

A team of marketing professionals with data scientists and IT professionals can communicate any queries related to the MLDC product with the vendors. A data scientist would be more interested in knowing the technical features of the software. A marketing manager would be curious to know how the marketing team could use MLDC for any project. An IT professional would want to understand the software installation procedure.

**Negotiation**

Once the vendor quotes the price, the negotiations begin. The price is fixed based on the cost of other similar products available in the market and the extent to which the product can solve the challenges.

**Final decision**

The final decision is based on agreements between the vendor and the buyer.