A Metadata Platform for the Modern Data Stack
Data ecosystems are diverse — too diverse. DataHub's extensible metadata platform enables data discovery, data observability and federated governance that helps you tame this complexity.
Open Source
DataHub was originally built at LinkedIn and subsequently open-sourced under the Apache 2.0 License. It now has a thriving community with over a hundred contributors, and is widely used at many companies.
Forward Looking Architecture
DataHub follows a push-based architecture, which means it's built for continuously changing metadata. The modular design lets it scale with data growth at any organization, from a single database under your desk to multiple data centers spanning the globe.
Massive Ecosystem
DataHub has pre-built integrations with your favorite systems: Kafka, Airflow, MySQL, SQL Server, Postgres, LDAP, Snowflake, Hive, BigQuery, and many others. The community is continuously adding more integrations, so this list keeps getting longer and longer.
Trusted Across the Industry
Supported integrations
How does it work?
Automated Metadata Ingestion
Push-based ingestion can use a prebuilt emitter or can emit custom events using our framework.
Pull-based ingestion crawls a metadata source. We have prebuilt integrations with Kafka, MySQL, MS SQL, Postgres, LDAP, Snowflake, Hive, BigQuery, and more. Ingestion can be automated using our Airflow integration or another scheduler of choice.
DataHub's push-based architecture also supports pull, but pull-first systems cannot support push. Learn more about metadata ingestion with DataHub in the docs.
source: type: "mysql" config: username: "datahub" password: "datahub" host_port: "localhost:3306"sink: type: "datahub-rest" config: server: 'http://localhost:8080'datahub ingest -c recipe.yml
Discover Trusted Data
Browse and search over a continuously updated catalog of datasets, dashboards, charts, ML models, and more.
Understand Data in Context
DataHub is the one-stop shop for documentation, schemas, ownership, lineage, pipelines and usage information. Data quality and data preview information coming soon.
