A unified open-source metadata platform for data discovery, observability, and governance with column-level lineage and team collaboration.
OpenMetadata is a unified metadata platform that provides data discovery, data observability, and data governance capabilities through a central metadata repository. It solves the problem of fragmented metadata across different data tools by offering column-level lineage, team collaboration features, and an ingestion framework with 84+ connectors to various data sources.
Data engineers, data stewards, and data platform teams in organizations that need to manage, discover, and govern metadata across diverse data warehouses, databases, dashboards, and pipeline services.
Developers choose OpenMetadata for its comprehensive feature set covering discovery, observability, and governance in one open-source platform, its extensive connector ecosystem, and its strong community-driven development based on open metadata standards.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.
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Supports ingestion from 84+ data sources including warehouses, databases, and dashboards, as highlighted in the connectors section, enabling broad metadata coverage.
Allows defining and running data quality tests without coding, with interactive dashboards for results, making it accessible for non-technical users.
Provides data domains, ownership assignment, and automated classification using tags and terms, facilitating policy enforcement across organizations.
Built on open metadata standards and APIs, ensuring interoperability and extensibility, as per the philosophy section, reducing vendor lock-in.
Requires self-hosting with Docker or Kubernetes, involving significant setup and ongoing maintenance without a managed cloud option, as indicated in the installation instructions.
Relies on community channels like Slack for support, which may lack the responsiveness and SLAs of commercial solutions with dedicated teams.
With a central metadata store and numerous connectors, scaling to very large metadata volumes might require careful tuning and infrastructure planning, not addressed in the README.