# Best Machine Learning Data Catalog Software

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

**Total Products under this Category:** 88

### Category Stats (Aug 2026)

- **Average Rating:** 4.37/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Cloudera (+2.21%) - Among all products in this category, Cloudera recorded the largest rating increase compared to last month

_Last updated: August 27, 2026_

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

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

- 30 Analysts and Data Experts
- 2,000+ Authentic Reviews
- 88+ 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=1886&focus%5B%5D=39669)

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

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=cloudera&focus%5B%5D=collibra)

**Sponsored**

### AWS Glue

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.

[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=2026-08-28T23%3A07%3A17Z&secure%5Bdisplayable_resource_id%5D=1383&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1383&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=40849&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%3Fsource%3Dsearch&secure%5Btoken%5D=8d53e26baeef20f31f3d87c17c25020a2889b460d9d7e4197ce380e4b1a4af54&secure%5Burl%5D=https%3A%2F%2Faws.amazon.com%2Fglue%2F%3Ftrk%3D5f10e0f2-36c8-4421-b616-5578db3fe15e%26sc_channel%3Ddisplay%2Bads&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:** 134

#### How Do G2 Users Rate Atlan?

- **Ease of Use:** 9.0/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 9.2/10 (Category avg: 8.5/10)
- **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** , making data collaboration smooth and accessible for all.
- Users appreciate Atlan's **exceptional data discovery and collaboration features** , simplifying data management and ensuring high quality.
- Users value Atlan for its **seamless data collaboration** , enhancing teamwork and making data management efficient and straightforward.
- Users value the **robust data cataloging** capabilities of Atlan, facilitating easy data discovery and collaboration.
- Users appreciate the **easy setup** of Atlan, enhancing productivity and collaboration without technical barriers.

##### Cons

- Users report **integration issues** with Teams and non-native databases, requiring more efficient setup and user management.
- Users face **dependency issues** with Atlan's tools, impacting functionality and limiting integration capabilities.
- Users find the **limited customization** options in Atlan restrictive, affecting adaptability for specific team workflows.
- Users experience **slow technical support** and inaccuracies, impacting the overall effectiveness and user satisfaction with Atlan.
- Users find **user interface issues** hinder usability, with limited customization and a steep learning curve for business 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: 8.5/10)
- **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 for data preparation and ETL operations.
- Users value the **s seamless data integration** capabilities of AWS Glue, enhancing efficiency across analytics and application development.
- Users appreciate the **fully managed ETL service** of AWS Glue, enjoying seamless integration and ease of use.
- Users appreciate the **versatile functionality** of AWS Glue, simplifying data discovery, preparation, and analytics integration.
- Users appreciate the **ease of implementation** and effective support of AWS Glue for seamless data integration and error tracing.

##### Cons

- Users experience **slow performance** with AWS Glue, particularly in startup times and complex debugging processes.
- Users face **difficulties in debugging** AWS Glue due to unclear error messages and a steep learning curve.
- Users often face **difficult debugging** with AWS Glue, as error messages are not always clear and can be frustrating.
- Users experience **performance issues** with AWS Glue, such as slow startup times and complex debugging processes.
- Users note that **AWS Glue can be time-consuming** due to slow startup times and complex debugging processes.

#### 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:** 90

#### 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: 8.5/10)
- **Metadata Management :** 7.9/10 (Category avg: 8.4/10)
- **Data Lineage:** 7.3/10 (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)  
586 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 58% Large, 27% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users praise Alation for its **ease of use** , facilitating data exploration and enhancing overall efficiency in data management.
- Users value the **flexible data discovery** features of Alation, enhancing governance and improving data interpretation.
- Users appreciate the **intuitive navigation** of Alation, making information retrieval quick and enhancing productivity significantly.
- Users find Alation's **data cataloging features** invaluable for efficient data exploration and enhanced trust in data quality.
- Users appreciate the **intuitive user interface** of Alation, making navigation and information retrieval remarkably efficient.

##### Cons

- Users report **slow performance** when integrating multiple data sources and loading larger datasets, impacting overall efficiency.
- Users feel Alation lacks **mature AI features** and faces issues with data profiling and inconsistent lineage analytics.
- Users note the **limited functionality** of Alation, particularly with the restricted features in non-enterprise licenses.
- Users face significant **lineage limitations** , including bugs and inconsistencies that hinder effective data management across systems.
- Users experience **user interface issues** with Alation, particularly slow navigation and a less intuitive design for newcomers.

#### 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: 8.5/10)
- **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?

**["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)

**["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)

### [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:** 113

#### 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: 8.5/10)
- **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, 36% 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, facilitating collaboration and clarity in data visualization.
- Users value the **ease of collaboration** in erwin Data Modeler, enhancing alignment between technical and business teams.
- Users appreciate the **clarity in designing and visualizing database structures** with erwin Data Modeler, enhancing collaboration and reducing errors.
- Users value the **ease of use for data governance** in erwin Data Modeler, facilitating better collaboration and reporting.
- Users value the **seamless data management** capabilities of erwin Data Modeler across various environments and data sources.

##### Cons

- Users find the **licensing costs high** , prompting many to switch to more affordable data modeling solutions.
- Users find the **complexity** of erwin Data Modeler challenging, especially for new users navigating its outdated interface.
- Users find the **difficult interface** of erwin Data Modeler challenging, especially for newcomers to data modeling.
- Users find the **limited customization** options of erwin Data Modeler restrict their experience and flexibility in design.
- Users find the **outdated design** of erwin Data Modeler makes it challenging for new users to adapt quickly.

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

**["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)

**["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)

#### 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: 8.5/10)
- **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 and engaging diversity** of tasks on Appen, enhancing their work experience and enjoyment.
- Users appreciate the **ease of use** of Appen, allowing task completion conveniently via their cell phones.
- Users appreciate the **flexibility** of Appen, allowing them to engage in diverse and interesting projects.

##### Cons

- Users experience frequent **work interruptions** due to inconsistent project availability and navigation issues, affecting income reliability.
- Users find the **low compensation** and inconsistent work availability makes Appen unreliable for a steady income.
- Users find the **navigation confusing** and experience frequent logouts, impacting their usability of Appen.
- Users often experience **connectivity issues** with Appen, leading to confusion and frequent disconnections.
- Users find the **navigation confusing** and report frequent disconnections, impacting their overall experience with Appen.

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

**["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)

**["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)

### [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:** 4.2/5.0

**Total Reviews:** 187

#### 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: 8.5/10)
- **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, Banking
- **Company Size:** 39% Large, 36% Small

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

_AI-generated summary from verified user reviews_

##### Pros

- Users praise the **user-friendly interface** of Cloudera, highlighting its simplicity in managing big data efficiently.
- Users value the **easy scalability** of Cloudera, enabling efficient management of large amounts of data effortlessly.
- Users value the **robust security features** of Cloudera, ensuring safe and reliable data management across platforms.
- Users value the **comprehensive suite of tools** in Cloudera for effective data management and analytics.
- Users find Cloudera's **scalability and centralized administration** invaluable for efficient monitoring and management of data processes.

##### Cons

- Users express concerns over the **high costs** of Cloudera, noting it's expensive for its complexity and maintenance.
- Users find Cloudera's database to be **complex** , making it challenging for inexperienced professionals to utilize effectively.
- Users find Cloudera's setup **difficult to learn** , particularly challenging for beginners without adequate tutorials or guidance.
- Users find the **poor documentation** of Cloudera frustrating, complicating navigation and setup for complex data configurations.
- Users often face **access issues** with Cloudera, particularly with unauthorized errors in Airflow tasks and limited documentation.

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

**["Streamlined Migration, Excellent Usability"](https://www.g2.com/survey_responses/cloudera-review-13333837)**

**Rating:** 4.0/5.0 stars

_— mohan t._

[Read full review](https://www.g2.com/survey_responses/cloudera-review-13333837)

**["Fast Platform with Quality Tools and Advanced Tech Stack"](https://www.g2.com/survey_responses/cloudera-review-13332785)**

**Rating:** 4.0/5.0 stars

_— Chess G._

[Read full review](https://www.g2.com/survey_responses/cloudera-review-13332785)

#### 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)

### [Informatica Data & AI Governance, Privacy](https://www.g2.com/products/informatica-data-ai-governance-privacy/reviews)

Informatica Data & AI Governance, Privacy is a comprehensive, cloud-native solution designed to empower organizations with predictive data intelligence. By integrating data discovery, cataloging, governance, and lineage capabilities, it enables businesses to find, understand, trust, and access their data assets efficiently. This unified approach simplifies collaboration between technical and business teams, ensuring that data-driven decisions are based on accurate and trustworthy information. With AI-powered automation, the platform enhances data classification, curation, and quality management, facilitating faster and more reliable analytic insights. By providing a holistic view of data relationships and lineage, Informatica Cloud Data Governance and Catalog helps organizations turn their data into a competitive advantage. Key Features and Functionality: - Automated Data Discovery and Classification: Utilizes AI to automatically find, classify, and inventory critical data across cloud and on-premises environments. - Comprehensive Data Cataloging: Creates a centralized repository of data assets, linking technical metadata with business context for enhanced understanding. - End-to-End Data Lineage: Provides visual representations of data flow and transformations, enabling users to trace data origins and assess impact. - Integrated Data Quality Management: Monitors and ensures data quality through profiling, validation, and cleansing processes. - Collaboration and Social Curation: Facilitates teamwork by allowing users to share insights, certify data assets, and engage in discussions through comments and ratings. - AI Model Governance: Manages and governs AI models alongside data, ensuring compliance and trust in AI-driven decisions. Primary Value and Problem Solved: Informatica Data & AI Governance, Privacy addresses the critical need for organizations to manage and govern their data assets effectively in an increasingly complex data landscape. By providing a unified platform that automates data discovery, classification, and quality management, it ensures that businesses can trust their data for decision-making. The solution enhances collaboration between technical and business users, linking technical metadata with business context to provide a holistic view of data assets. This comprehensive approach not only accelerates the delivery of reliable analytic insights but also ensures compliance with data governance policies, ultimately turning data into a strategic asset that drives innovation and competitive advantage.

**Average Rating:** 4.1/5.0

**Total Reviews:** 115

#### How Do G2 Users Rate Informatica Data & AI Governance, Privacy?

- **Ease of Use:** 8.2/10 (Category avg: 8.6/10)
- **Business and Data Glossary:** 8.1/10 (Category avg: 8.5/10)
- **Metadata Management :** 8.1/10 (Category avg: 8.4/10)
- **Data Lineage:** 8.6/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Informatica Data & AI Governance, Privacy?

- **Seller:** [Informatica](https://www.g2.com/sellers/informatica)
- **Company Website:** www.informatica.com
- **Year Founded:** 1993
- **HQ Location:** Redwood City, CA
- **Twitter:** @Informatica  
99,643 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=06f93f9659c25422bea5c34037117512928a659c5d640bb989ed85a85cdb1252&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3858%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,802 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 49% Large, 29% Small

#### What Do G2 Reviewers Say About Informatica Data & AI Governance, Privacy?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **automatic discovery and governance** of enterprise data, enhancing clarity and trust in data management.

##### Cons

- Users often face **integration issues** due to complex setup and design, especially in large enterprises with legacy systems.

#### What Are Recent G2 Reviews of Informatica Data & AI Governance, Privacy?

**["Data governance is must for every organisation growth"](https://www.g2.com/survey_responses/informatica-data-ai-governance-privacy-review-7944534)**

**Rating:** 5.0/5.0 stars

_— Prakash U._

[Read full review](https://www.g2.com/survey_responses/informatica-data-ai-governance-privacy-review-7944534)

**["Consultant"](https://www.g2.com/survey_responses/informatica-data-ai-governance-privacy-review-10306195)**

**Rating:** 4.5/5.0 stars

_— Himanshu S._

[Read full review](https://www.g2.com/survey_responses/informatica-data-ai-governance-privacy-review-10306195)

#### What Are G2 Users Discussing About Informatica Data & AI Governance, Privacy?

- [What is Informatica Enterprise Data Catalog used for?](https://www.g2.com/discussions/what-is-informatica-enterprise-data-catalog-used-for)
- [What is Informatica Dynamic Data Masking used for?](https://www.g2.com/discussions/what-is-informatica-dynamic-data-masking-used-for)
- [What is Informatica Data Privacy Management used for?](https://www.g2.com/discussions/what-is-informatica-data-privacy-management-used-for)
- [What is Privitar Data Privacy Platform used for?](https://www.g2.com/discussions/what-is-privitar-data-privacy-platform-used-for)
- [What is Big Data Governance Edition used for?](https://www.g2.com/discussions/what-is-big-data-governance-edition-used-for)

### [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: 8.5/10)
- **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 appreciate the **unified data intelligence platform** of Collibra, effectively aligning Business and IT on a single system.
- Users value the **strong data governance** features of Collibra, enhancing data accessibility and trustworthiness across the organization.
- Users value the **effective data management** capabilities of Collibra, enhancing compliance, governance, and integration for optimal use.
- Users appreciate the **collaborative tools** of Collibra, enhancing communication and efficiency in managing complex data ecosystems.
- Users value Collibra for its **reliable and user-friendly data intelligence platform** , enhancing productivity through seamless integration and support.

##### Cons

- Users note the **complexity issues** in Collibra, particularly with setup, bugs, and inconsistent API stability.
- Users find Collibra's **complexity** hinders efficiency, as setup, configuration, and user engagement can be overwhelming.
- Users struggle with **limited functionality** due to complex navigation and unintuitive language in Collibra.
- Users find the **difficult setup** of Collibra to require significant time and resources, impacting their overall experience.
- Users find Collibra to be **expensive** , with high licensing fees and challenges in adoption impacting user experience.

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

**["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)

**["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)

#### 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)

### [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: 8.5/10)
- **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 appreciate the **intuitive and efficient UI** of Decube, simplifying data monitoring and issue detection.
- Users appreciate the **ease of use** of Decube, enjoying its user-friendly interface and seamless data monitoring.
- Users love the **visibility into data pipelines** provided by Decube, enabling early detection of issues and reliable data management.
- Users value Decube for its **robust data quality features** , ensuring early detection of issues and reliable data management.
- Users value Decube for its **clear insights and easy data monitoring** , making it simple to manage data pipelines effectively.

##### Cons

- Users find the **limited functionality** of decube frustrating, as deeper insights require extra effort and manual configuration.
- Users find the **complex setup** of Decube time-consuming and occasionally overwhelming during initial configuration.
- Users find the **limited features** of Decube require extra effort for deeper insights and configurations.
- Users find the **missing features** in Decube, such as API monitoring and group-by options, frustrating and limiting.
- Users frequently experience **poor customer support** , often finding it difficult to reach assistance when needed.

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

**["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)

**["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)

### [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: 8.5/10)
- **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 praise the **ease of use** of Select Star, allowing effortless integration and efficient data management.
- Users value the **insightful data lineage** offered by Select Star, enhancing understanding and management of data effectively.
- Users value the **clean and intuitive UI** of Select Star, enhancing data discovery and simplifying complex tasks.
- Users value the **easy data discovery** features of Select Star, significantly simplifying navigation in complex data models.
- Users value the **ease of data discovery** in Select Star, enhancing their ability to locate and analyze metadata efficiently.

##### Cons

- Users find **limited functionality** in Select Star, wishing for broader insights and enhanced reporting capabilities.
- Users face **lineage limitations** with Select Star, struggling to visualize dependencies and access permissions in complex queries.
- Users note a **complex setup** for Select Star, especially in configuring a unified project for dbt mesh ecosystems.
- Users find **difficult learning** curves with Select Star, requiring clearer guidance for quicker value extraction.
- Users find the **expertise required** for Select Star to be a barrier, seeking more accessible guidance for faster value.

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

**["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)

**["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)

### [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)

### [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: 8.5/10)
- **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 improving asset discovery across teams.
- Users praise Secoda's **easy onboarding** and self-serve nature, enhancing data governance and user empowerment from day one.
- Users value the **integration capabilities** of Secoda, seamlessly connecting with numerous platforms for enhanced data management.
- Users appreciate the **ease of learning** with Secoda, noting its intuitive design and supportive resources for all users.
- Users praise the **helpful data lineage and questions features** of Secoda for enhancing knowledge sharing and understanding.

##### Cons

- Users find the **learning difficulty** with integrations and team systems to be a frustrating barrier to effective usage.
- Users note that Secoda has **product immaturity** , with occasional bugs and a lack of some essential features.
- Users express concerns over **improvement needed** for filtering assets, AI model descriptions, and overall user experience in Secoda.
- Users find Secoda has **limited functionality** with an overwhelming interface and insufficient support for essential features.
- Users report **performance issues** in Secoda, including syncing delays and frequent bugs affecting functionality and user experience.

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

**["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)

**["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)

### [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: 8.5/10)
- **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 find Coalesce Catalog's **ease of use** exceptional, simplifying data discovery and enhancing collaboration across teams.
- Users appreciate the **collaboration features** of Coalesce Catalog, enhancing knowledge sharing and onboarding processes.
- Users appreciate the **seamless connectivity** of Coalesce Catalog, simplifying data discovery and integration across various sources.
- Users find the **data lineage feature** invaluable for simplifying data discovery and enhancing team collaboration.
- Users find the **lineage feature** extremely useful for simplifying data discovery and enhancing connectivity across data sources.

##### Cons

- Users face **connector issues** that prevent direct integration of other AI agents with the Coalesce Catalog knowledge.
- Users face **integration issues** , as connecting other AI agents to the Catalog knowledge is not possible.
- Users face a **limitation in AI integration** as connecting other agents directly to the Catalog knowledge is not possible.

#### 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)

### [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: 8.5/10)
- **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 love the **ease of use in data analytics** with data.world, making data discovery enjoyable and straightforward.
- Users value the **ease of data discovery and analytics** , enhancing their overall experience with data.world.
- Users value the **discoverability and ease of use** in data management with data.world, enhancing data analytics efficiency.
- Users enjoy the **easy-to-use data visualization** tools, making data discovery and analytics accessible and enjoyable.
- Users enjoy the **ease of use** of data.world, making data discovery and analytics accessible and enjoyable.

##### Cons

- Users often face **poor customer support** , leading to frustration when resolving issues or queries with data.world.
- Users experience **poor support services** , leading to frustration when troubleshooting their issues on data.world.

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

**["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)

**["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)

#### 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

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[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

### Machine Learning Data Catalog Topics

- [What is a Machine Learning Data Catalog?](#what-is-a-machine-learning-data-catalog)
- [What does MLDC Stand For?](#what-does-mldc-stand-for)
- [What are the Common Features of Machine Learning Data Catalogs?](#what-are-the-common-features-of-machine-learning-data-catalogs)
- [What are the Benefits of Machine Learning Data Catalogs?](#what-are-the-benefits-of-machine-learning-data-catalogs)
- [Who Uses Machine Learning Data Catalogs?](#who-uses-machine-learning-data-catalogs)
- [Challenges with Machine Learning Data Catalogs](#challenges-with-machine-learning-data-catalogs)
- [How to Buy Machine Learning Data Catalogs](#how-to-buy-machine-learning-data-catalogs)

[
### Machine Learning Data Catalog Topics
 Expand/Collapse ](#)
- [What is a Machine Learning Data Catalog?](#what-is-a-machine-learning-data-catalog)
- [What does MLDC Stand For?](#what-does-mldc-stand-for)
- [What are the Common Features of Machine Learning Data Catalogs?](#what-are-the-common-features-of-machine-learning-data-catalogs)
- [What are the Benefits of Machine Learning Data Catalogs?](#what-are-the-benefits-of-machine-learning-data-catalogs)
- [Who Uses Machine Learning Data Catalogs?](#who-uses-machine-learning-data-catalogs)
- [Challenges with Machine Learning Data Catalogs](#challenges-with-machine-learning-data-catalogs)
- [How to Buy Machine Learning Data Catalogs](#how-to-buy-machine-learning-data-catalogs)

## Learn More About Machine Learning Data Catalog 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.