Side by side
DataHub vs Marquez
Both stand on active metadata management software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan Open source APILinuxMac+3
DataHub combines metadata discovery, lineage, and observability, with a choice of self-hosted or managed deployment. Core is free to deploy; teams considering Cloud should account for use-based pricing and its managed support model.
Visit DataHub Free plan APILinuxMac+3
Choose Marquez if your data team needs an open-source system for collecting OpenLineage metadata and tracing dependencies across jobs and datasets. Look elsewhere if you need column lineage beyond Spark or require API authentication enabled by default.
Visit MarquezThe facts
| DataHub | Marquez | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Yes | Not published |
| Runs on | API, Linux, Mac, Self-hosted, Web, Windows | API, Linux, Mac, Self-hosted, Web, Windows |
| Lowest paid plan | Free or on request | Not published |
| Plans published | 2 | None |
| Maker | Not published | Not published |
| Website | datahub.com | marquezproject.ai |
| On active metadata management software | #1 of 25 | #5 of 25 |
DataHub: what it does well
- Free, self-hosted Core option.
- Cloud includes more than 100 pre-built connectors.
- Column-level lineage spans sources and downstream assets.
- Cloud offers automated checks and anomaly detection.
- Cloud trial is advertised for 21 days.
What to know first
- Core requires users to manage installation and operations.
- Core lacks SSO and fine-grained permissions out of the box.
- Cloud pricing depends on data volume, users, and capabilities.
Marquez: what it does well
- Collect OpenLineage metadata from running jobs in real time.
- Inspect job inputs, outputs, lineage and execution details in a web UI.
- Query lineage and traverse dependencies through its API.
- Track dataset changes and job run history.
- Integrates with Airflow, Spark, Flink, dbt and Dagster through OpenLineage.
What to know first
- API authentication and authorization are off by default.
- Column lineage support is limited to the Spark integration.
- Deployment guidance uses PostgreSQL for metadata storage.
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