Datahub
Unified context graph for AI agents — metadata, lineage, data quality, and governance in one platform
| What is it | Unified context graph for AI agents — metadata, lineage, data quality, and governance in one platform |
|---|---|
| Pricing | Unknown |
| Platform | Web Application |
| API | Yes |
| Works with | Claude AI |
| Best for | unifying metadata and business context across the data estate, enabling AI agents with trusted data lineage and quality |
| Domain registered | 1995 |
Data updated Aug. 1, 2026
What does Datahub do?
Datahub is a context management platform that gives AI agents and data teams a single source of truth for metadata, lineage, data quality, and governance. It ingests structured data from systems like Snowflake and Databricks, unstructured data from Slack and Notion, and business context from Salesforce and Workday, then unifies everything into a context graph. That graph is served to AI agents (Claude, Cursor, LangChain, etc.) via MCP, APIs, and SDKs, so every agent has the same reliable context when answering questions or taking actions.
What makes Datahub stand out is how it keeps context fresh and trustworthy. It tracks lineage from pipeline to prompt, so you can see exactly where data came from and how a change ripples through. Data quality checks — freshness, volume, column-level — are delivered to agents at query time, not after the fact. The platform also derives context automatically from query logs and usage patterns, so you don't need a separate documentation project. Governance is built in: agents can propose new metric definitions, and experts review and approve them, with every decision feeding back into the system.
Datahub is built for enterprise data teams that need to scale AI safely. It's used by over 3,000 organizations and has an open-source community of 15,000+ members. The platform comes in two flavors: DataHub Core (the open-source metadata platform) and DataHub Cloud (the managed enterprise version with additional features like AI-powered discovery and automated governance). Real-world use cases include unifying metadata across a data lake, giving AI agents trusted lineage for compliance, and reducing data-related outages by 48% according to an IDC study.
Key features
What makes it stand outWho is Datahub for?
Who benefits most from this toolTrust & presence
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