# DataHub Reviews **Vendor:** DataHub **Category:** [Data Governance Tools](https://www.g2.com/categories/data-governance-tools) **Average Rating:** 4.4/5.0 **Total Reviews:** 8 ## About DataHub DataHub is an event-driven AI and Data Context Platform designed to unify discovery, governance, and observability across an organization’s entire data estate. Unlike traditional data catalogs, DataHub Cloud offers real-time updates, automatic policy enforcement, and seamless integration with over 100 data sources. This ensures that organizations can maintain data quality, compliance, and AI-readiness at scale, addressing the complexities of modern data management. Targeted at data teams, governance professionals, and AI practitioners, DataHub serves a diverse audience that includes data engineers, analysts, data stewards, and compliance officers. The platform is particularly beneficial for organizations that require a centralized source of truth for all metadata across various environments, such as data warehouses, lakes, business intelligence platforms, machine learning systems, and AI agents. By consolidating data management processes, DataHub enhances collaboration and efficiency within data teams, enabling them to work more effectively. One of the standout features of DataHub is its automated data lineage tracking, which operates down to the column level. This capability allows teams to quickly assess the impact of any upstream changes, facilitating faster debugging of quality issues and helping to avert costly incidents before they escalate to production. Additionally, the platform employs AI-powered functionalities to manage repetitive tasks associated with metadata, such as documentation generation, intelligent glossary classification, and sensitive data tagging. This automation empowers data professionals to concentrate on higher-value activities, thereby increasing overall productivity. For data governance and compliance teams, DataHub offers robust tools for continuous policy enforcement, role-based access controls, and personally identifiable information (PII) detection. The platform is designed to support regulatory standards such as GDPR, HIPAA, and PCI, all while minimizing manual oversight. This ensures that organizations can maintain compliance without the burden of extensive manual processes. Furthermore, for AI and ML teams, DataHub provides the reliable data context essential for developing trustworthy AI agents and models, fostering innovation and improving outcomes. With backing from prominent investors like Bessemer Venture Partners, LinkedIn, and 8VC, DataHub has gained the trust of leading organizations, including Netflix, Visa, Slack, and Pinterest. This widespread adoption underscores the platform's effectiveness in transforming data operations and enhancing the overall data management landscape. For more information, visit datahub.com. ## DataHub Pros & Cons **What users like:** - Users find DataHub **easy to use** , effectively organizing and sharing datasets with great connectivity to other tools. (3 reviews) - Users value the **connectivity** of DataHub, enabling seamless integration with numerous third-party tools effortlessly. (2 reviews) - Users appreciate the **ease of use and free accessibility** of DataHub, simplifying complex data lineage management. (2 reviews) - Users highlight the **accuracy** of DataHub, effectively simplifying complex data lineage for better insights. (1 reviews) - Users value the **affordability** of DataHub, especially appreciating its free, open-source nature and easy setup. (1 reviews) - Data Lineage (1 reviews) - Users love the **easy integrations** of DataHub Cloud, making data sharing and management seamless and efficient. (1 reviews) - Easy Setup (1 reviews) - Users value the **ease of use** and open source nature of DataHub Cloud for managing complex data lineage. (1 reviews) - Free Services (1 reviews) **What users dislike:** - Users struggle with **integration issues** in DataHub, particularly lacking support for DBT and data quality tests. (2 reviews) - Users face **dependency issues** with DataHub, requiring extra effort from data owners for effective utilization. (1 reviews) - Users find the **difficult interface** of DataHub can be clunky, impacting their overall experience despite its data display capabilities. (1 reviews) - Users express concern over the **lack of features** , including absence of data quality tests and dbt support. (1 reviews) - Users experience **slower performance with large datasets** , making data management more cumbersome than anticipated. (1 reviews) - Users report **poor UI** that complicates navigation and detracts from overall user experience in DataHub Cloud. (1 reviews) - Users experience **slow performance** when handling large datasets, making the process cumbersome and less efficient. (1 reviews) - User Difficulty (1 reviews) ## DataHub Reviews ### 1. Easy and Efficient Tool! **Rating:** 4.5/5.0 stars **Reviewed by:** Kessie M. | Data Entry Specialist - VA, Small-Business (50 or fewer emp.) **Reviewed Date:** January 29, 2025 **What do you like best about DataHub?** DataHub is simple to use and helps keep my data organized. It’s great for sharing and managing datasets, and the version control is a big plus. I’d definitely recommend it! **What do you dislike about DataHub?** Performance with Large Datasets: Sometimes, handling really large datasets can slow things down or be more cumbersome than expected. **What problems is DataHub solving and how is that benefiting you?** It’s great for keeping track of datasets, making it easy to find and access data across teams or organizations. It’s likely helping me manage my data in a more organized and collaborative way. ### 2. Easy to use data Catalog tool **Rating:** 4.0/5.0 stars **Reviewed by:** Siddharth N. | Senior Consultant, Mid-Market (51-1000 emp.) **Reviewed Date:** January 26, 2025 **What do you like best about DataHub?** It's an easy to use open source data catalog tool which helps solves the complex data lineage. **What do you dislike about DataHub?** Lacks support for DBT and test integrations **What problems is DataHub solving and how is that benefiting you?** I am using it for cataloging and tracking the data lineage. ### 3. Finding Lineage in easy and Best Way **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer & Network Security | Mid-Market (51-1000 emp.) **Reviewed Date:** March 24, 2023 **What do you like best about DataHub?** Ease of use and Connectivity with 3rd Party Tools **What do you dislike about DataHub?** Nothing as Serious, but integration with more analytics tools will be added advantage **What problems is DataHub solving and how is that benefiting you?** Recording Lineage ### 4. Great open source for starters **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** October 31, 2023 **What do you like best about DataHub?** Easy to setup Connected to wide number of tools Free to use - Open source **What do you dislike about DataHub?** - Cannot integrate data quality tests - Support for dbt **What problems is DataHub solving and how is that benefiting you?** - Visualization of all data assets - data governance - data discoverability ### 5. The beginning of deploying Datahub(especially metadata and docs) in our organization **Rating:** 3.5/5.0 stars **Reviewed by:** Or S. | Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2023 **What do you like best about DataHub?** I think the UI is making total sense. Almost every dataset from any platform we have looks the same on the UI, which is helping a lot with the adoption of this product. I think that the ability to map every data source and their lineage is extremely important for big organizations and can save lots of time for our employees. **What do you dislike about DataHub?** The thing with Datahub is that you have to put in some amount of time just to see if it can give your users value. and sometimes the work must come from the owners of the data(and not the Datahub owners) who don't necessarily have a clear interest in that work. **What problems is DataHub solving and how is that benefiting you?** Creating one place for our data guidelines/explanations/confluence pages. it saves time for our employees, reduces friction for the owners who created the data and it enables the possibility to enforce future documentations into this 'one place' ### 6. Sweet spot between features and pricing **Rating:** 5.0/5.0 stars **Reviewed by:** Ada D. | Mid-Market (51-1000 emp.) **Reviewed Date:** June 02, 2023 **What do you like best about DataHub?** When we were tasked with choosing a data cataloging solution, we compared several different companies, and no competitor came close to Acryl. Other solutions had slightly more features but came with a significantly higher cost and weren't open-source. **What do you dislike about DataHub?** The UI can feel clunky sometimes, but I appreciate how difficult it is to build a general-purpose UI to display datasets from so many different possible sources. **What problems is DataHub solving and how is that benefiting you?** Acryl hosts our DataHub instance that we use for all of our data cataloging and data governance needs. We've gone from a hodgepodge of tracking and documentation stores to a one-stop shop containing everything. ### 7. Datahub for metadata sourcing **Rating:** 4.5/5.0 stars **Reviewed by:** Aditya K. | Lead Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 17, 2022 **What do you like best about DataHub?** Datahub is opensource so you do not have pay for any licence. Datahub is by far the best for metadata analysis and lineage because it supports applications from different stack (both opensource and paid) and you can capture and analyse metadata, create lineages under a single ui. The ones that we have integrated with Datahub is spark, kafka , mongoDB, psql, elasticsearch,hive, big query and oracle **What do you dislike about DataHub?** So far, i have not found anything to dislike as this solution basically overcomes the limitations of other data governance services like Atlas, Cloudera Navigator etc. **What problems is DataHub solving and how is that benefiting you?** Single place for governance of multiple services of different stack like spark, kafka , mongoDB, psql, elasticsearch,hive, big query and oracle(refer to the screenshot). Analysing the metadata for audits and creating lineages under one umbrella. ### 8. Datahub review **Rating:** 5.0/5.0 stars **Reviewed by:** Vipin S. | Senior Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 18, 2022 **What do you like best about DataHub?** Datahub provides best service to integrate with all your systems and web applications. It's provides ability to make an easy system without any complexity which helps our users to do their day to day activities **What do you dislike about DataHub?** It's hard to find supportive documents and help from the website and sometimes support is not provided within the stipulated SLA which impacts production and ability to deliver **What problems is DataHub solving and how is that benefiting you?** A data hub is a centralized service that connects all of your IT systems, whether they be Web applications, IoT devices, SaaS solutions, or core business platforms, such as CRM or ERP that manages the connections to each of the systems and orchestrates the data flow amongst them - [View DataHub pricing details and edition comparison](https://www.g2.com/products/datahub/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-14+22%3A47%3A05+-0500&secure%5Bsession_id%5D=3d1ea786-5dee-4805-8fc0-241f5dae0eca&secure%5Btoken%5D=984a960e61d64e3aa1c7ce14a394874aadbb3845308bd18a97392f2d690cb9f6&format=llm_user) ## DataHub Features **Data Governance** - User Access Management - Dynamic Data Masking - Data Lineage **Administration** - Data Modelling - Recommendations - Workflow Management - Dashboards and Visualizations **Management** - Business Glossary - Data Discovery - Data Profililng - Reporting and Visualization - Data Lineage **Data management** - Metadata Management - Automation Features - Collaboration - Data Lineage - Data Discovery **Data Preparation** - Search - Data Quality and Cleansing - Data Transformation - Data Modeling **Compliance** - Sensitive Data Compliance - Training and Guidelines - Policy Enforcement - Compliance Monitoring **Security** - Access Control - Roles Management - Compliance Management **Reporting** - Intelligent Insights - Actionable Insights - Dashboards **Collaboration** - Commenting - Profiling and Classification - Business and Data Glossary - Metadata Management **Data Quality** - Data Preparation - Data Unification **Maintainence** - Data Quality Management - Policy Management **Generative AI** - AI Text Generation - AI Text Summarization **Artificial Intelligence** - Machine Learning Recommendations - Natural Language Query - Automatic Data Cleansing **Functionality** - Identification - Correction - Normalization - Preventative Cleaning - Data Matching **Generative AI** - AI Text Generation - AI Text Summarization **Management** - Reporting - Automation - Quality Audits - Dashboard - Governance **Generative AI** - AI Text Generation - AI Text Summarization **Agentic AI - Data Governance** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Decision Making **Generative AI** - AI Text Generation - AI Text Summarization **Agentic AI - Machine Learning Data Catalog** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Decision Making ## Top DataHub Alternatives - [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) - 4.3/5.0 (754 reviews) - [Demandbase One](https://www.g2.com/products/demandbase-one/reviews) - 4.4/5.0 (1,891 reviews) - [Egnyte](https://www.g2.com/products/egnyte/reviews) - 4.5/5.0 (1,130 reviews)