What Is OpenMetadata? The Open-Source Metadata Platform Explained

OpenMetadata is an open-source platform for cataloging, discovering, and governing data. It collects metadata from across your data stack into a single graph, so teams can find datasets, read their definitions, see who owns them, and trace how they connect. It is released under the permissive Apache 2.0 license, which means the software itself is free to download and self-host.

The project was open-sourced in 2021 by a team that had built metadata systems at Uber (internally known as uMetadata and Databook). Today it is one of the most widely adopted open-source data catalog projects, with an active community and more than 120 connectors to warehouses, databases, dashboards, and pipelines.

What Is OpenMetadata?

OpenMetadata is best understood as a central place where the metadata about your data lives. Instead of definitions, ownership, and lineage being scattered across spreadsheets, wiki pages, and individual tools, OpenMetadata pulls them into one searchable graph that both technical and business users can browse.

It sits in the same category as commercial data catalogs, but takes an open-source, API-first approach. Every metadata entity (a table, a column, a dashboard, a pipeline, an owner) is defined by a published JSON schema, and everything the user interface does is also available through the API. That design makes the platform extensible: teams can add custom properties, model new entity types, and integrate metadata operations into their own systems.

The platform spans the core functions you would expect from a modern catalog: search and discovery, a business glossary, classification and tagging, column-level lineage, data quality tests, and collaboration features like ownership, descriptions, and announcements.

Architecture: How OpenMetadata Works

OpenMetadata runs on a relatively compact architecture with a small number of moving parts. Four components do the work:

• Metadata server (API). A Java-based backend that stores and serves metadata through a schema-first REST API. This is the heart of the system.
• Ingestion framework. A Python framework that runs connectors to pull metadata from source systems on a schedule. The 120-plus connectors cover warehouses, databases, BI tools, pipelines, and data quality tools.
• User interface. A JavaScript and TypeScript web application for search, browsing, lineage views, and collaboration.
• Storage layer. A relational database (MySQL or PostgreSQL) holds the metadata, and a search index (Elasticsearch or OpenSearch) powers fast discovery. Notably, OpenMetadata uses a relational database rather than a dedicated graph database.

Metadata flows in one direction: connectors extract metadata from your sources, the ingestion framework normalizes it against the published schemas, the server stores it, and the UI and API serve it back to users and downstream tools.

Key Features

OpenMetadata covers the full set of capabilities a data team expects from a catalog:

• Unified metadata graph. Technical, operational, quality, lineage, and governance metadata for every asset live together, so a single view connects a table to its owner, its tests, its upstream pipelines, and its glossary terms.
• Search and discovery. Users search across tables, columns, dashboards, and pipelines, read descriptions, and identify owners. This is the data discovery layer.
• Column-level lineage. Automated data lineage traces how data flows from source to report, including at the column level, which helps with impact analysis and debugging.
• Business glossary and classification. A shared business glossary plus tags and classifications (including for sensitive data) connect technical assets to business meaning.
• Data quality and profiling. Built-in tests and profilers track freshness, null rates, and other quality signals over time.
• Collaboration and governance. Ownership, descriptions, announcements, and activity feeds support data governance workflows directly in the platform.

Because OpenMetadata is built on an extensible schema, teams can also model custom entities and properties that the standard catalog does not ship with. This is part of what makes it active metadata friendly: metadata is not just stored, it can drive automation through the API.

What "Open Source" Means Here

OpenMetadata's core is genuinely open source under Apache 2.0. You can download it, run it, modify it, and extend it at no license cost. For engineering-led teams that want full control and a code-first integration model, this is a strong fit.

The distinction worth understanding is that free software is not the same as free to operate. Running OpenMetadata in production means standing up and maintaining the server, the ingestion jobs, the relational database, and the search index, then handling upgrades, backups, security, and uptime over time. That operational work is an engineering cost, not a license cost.

For teams that want OpenMetadata without that operational burden, Collate, the company founded by the project's creators, offers a managed cloud service. The trade-offs between self-hosting and managed services, and what each actually costs, are covered in detail in the companion article on OpenMetadata pricing.

Who Uses OpenMetadata

OpenMetadata fits best in specific situations:

• Engineering-led data teams that want an open, API-first catalog they can extend and embed in their own platform.
• Organizations standardizing on open source for strategic or cost reasons, and that have the platform engineering capacity to run it.
• Teams that need broad technical lineage and metadata coverage across many sources, and value the 120-plus connectors.

It is a weaker fit where the primary audience is business users who need a polished, low-friction experience without engineering support, or where the organization lacks the platform team to own a self-hosted deployment. In those cases, a managed, business-friendly catalog usually drives faster adoption.

OpenMetadata vs a Governed, Managed Catalog

OpenMetadata and Dawiso solve the same problem from different angles. OpenMetadata gives engineering teams an open, self-hosted toolkit they assemble and operate themselves. Dawiso is a managed, business-friendly platform designed so that non-technical users adopt it quickly, without a platform team to keep it running.

The practical differences show up in three places. First, ownership of operations: with OpenMetadata your team runs the infrastructure; with Dawiso the platform is delivered as a service. Second, audience: OpenMetadata is API-first and engineer-oriented, while Dawiso prioritizes the business glossary and a workflow built for business users. Third, AI-readiness: Dawiso serves governed context to AI agents through the Model Context Protocol (MCP), so trusted definitions and lineage become available to any MCP-compatible assistant.

Neither approach is universally better. The right choice depends on whether you want to own and extend an open-source toolkit, or adopt a governed catalog that business teams use without engineering overhead. For a side-by-side view, see the Dawiso vs OpenMetadata comparison.

Conclusion

OpenMetadata is a capable, open-source metadata management platform with a clean architecture, broad connector coverage, and an API-first design that engineering teams can extend. Its core is free under Apache 2.0, which makes it attractive on paper, but production use carries real operational cost. Before committing, weigh the engineering effort of self-hosting against managed alternatives, and read the companion guide on OpenMetadata pricing to understand what "free" actually means in total cost.