Open Source Data Catalog: The 8 Best Options for 2026

An open source data catalog is a metadata management platform released under a permissive license (Apache 2.0, MIT, or similar) that teams can self-host without per-seat fees. The eight leading options in 2026 are Data Workers, OpenMetadata, DataHub, Amundsen, Apache Atlas, Marquez, CKAN, and Magda.

Each catalog has different strengths depending on whether you prioritize AI-native access via MCP, real-time streaming lineage, simplicity for small teams, or heavyweight regulatory compliance. This guide compares all eight on architecture, ecosystem, and the workloads where each one wins.

This guide compares all eight so you can choose the right fit without wading through vendor marketing. We include license, GitHub stars, connector counts, and a decision framework at the end.

Why Choose an Open Source Data Catalog?

Teams pick open source catalogs for five reasons: cost control, no vendor lock-in, regulatory preference for self-hosting, ability to customize, and fast iteration with a community. Paid catalogs like Atlan, Collibra, and Alation cost $30-200 per user per month at scale — open source alternatives turn that into an infrastructure bill plus platform engineering effort.

The trade-off: you own the operations. A well-run open source catalog needs a dedicated platform engineer for upgrades, connector maintenance, and user support.

The 8 Best Open Source Data Catalogs

1. Data Workers — Apache 2.0. The newest open-source catalog and the only MCP-native one. 14 autonomous agents expose catalog, governance, quality, and lineage as MCP tools Claude Code and ChatGPT can call. Best for AI-first data teams.

2. OpenMetadata — Apache 2.0. Originally built at Uber. 75+ connectors, column-level lineage, clean UI. The most active open-source catalog community in 2026. Best for general-purpose cataloging.

3. DataHub — Apache 2.0. Built at LinkedIn. Streaming metadata via Kafka, strong GraphQL API. Best for teams that want real-time metadata updates.

4. Amundsen — Apache 2.0. Built at Lyft. Lightweight, PageRank-based search. Best for small teams that want a simple catalog with minimal ops.

5. Apache Atlas — Apache 2.0. Born in the Hadoop ecosystem. Strong lineage and classification. Best for teams still running on-prem Hadoop or CDH.

6. Marquez — Apache 2.0. The OpenLineage reference implementation. Pure lineage focus, not a full catalog. Best when you only need lineage.

7. CKAN — AGPL. Mature, government-sector favorite. Used by data.gov and many open data portals. Best for public data catalog use cases.

8. Magda — Apache 2.0. Australian government project. Federated catalog with strong ODK (open data kit) roots. Best for federated multi-source catalogs.

What to Evaluate Before Choosing

• •Connector coverage — Does it support your warehouse, BI, and transformation tools?
• •License compatibility — AGPL (CKAN) is incompatible with some commercial products
• •Community activity — Check GitHub commits, issues, and contributor count in the last 90 days
• •Deployment complexity — Docker Compose for dev, Helm for prod
• •AI agent access — Does it expose MCP tools for agents, or only REST APIs?
• •Column-level lineage — Minimum bar in 2026; table-only lineage is not enough

How Data Workers Differs From Other Open Source Data Catalogs

Data Workers is the only open source data catalog designed from day one for AI agents. While OpenMetadata and DataHub have REST APIs that agents can technically call, Data Workers exposes every catalog operation as an MCP tool — meaning Claude Code, Cursor, and ChatGPT can discover tables, trace lineage, and enforce governance policies through natural language.

This matters because AI agents are the fastest-growing data consumer class in 2026. A catalog that is easy for humans but hard for agents will be a bottleneck by 2027. Read the MCP data stack guide for context, or see the product docs for the full MCP tool list.

The right open source data catalog depends on your priorities. For general cataloging, OpenMetadata is the safe pick. For AI-native teams, Data Workers is the only option built for MCP. For real-time streaming, DataHub. For lightweight simplicity, Amundsen. Book a demo to see how Data Workers adds MCP-native access to any catalog you already run.