Marquez is an open-source metadata service designed for collecting, aggregating, and visualizing metadata across a data ecosystem. It focuses on maintaining the lineage of how datasets are consumed and produced, offering insights into job runtime and dataset access patterns. Marquez centralizes dataset lifecycle management and provides both a GraphQL and HTTP API for metadata access. It uses OpenLineage as its primary data model.
Marquez distinguishes itself through its comprehensive metadata collection capabilities and seamless integration with OpenLineage. It provides a user-friendly web UI for exploring data lineage and offers flexibility through both GraphQL and HTTP APIs. Its modular architecture supports extensibility and allows for graceful degradation in the face of changing technologies.
- Data Lineage: Tracks the flow of data between datasets and jobs, providing a visual representation of data dependencies.
- OpenLineage Integration: Built on top of the OpenLineage specification, ensuring interoperability and adherence to industry standards.
- GraphQL API: Enables flexible and efficient querying of metadata using the GraphQL query language.
- HTTP API: Provides standard RESTful endpoints for accessing and managing metadata.
- Docker Support: Easily deployable using Docker containers for simplified setup and management.
- Scalability: Designed to handle large and complex data ecosystems.
- Developer Experience: Well-documented with a focus on ease of use and extensibility.
Marquez is a graduated project under active development and maintenance. It has a growing community and a stable API, with regular updates and bug fixes. The project maintains compatibility with OpenLineage 2.0-2 and is actively following the latest specifications. The documentation is comprehensive and aims to guide users through various deployment and integration scenarios.
Marquez benefits data engineers, data scientists, and data governance professionals. It addresses challenges related to data discovery, lineage tracking, and data quality. By providing a centralized view of the data ecosystem and simplifying metadata management, Marquez offers significant value compared to manual tracking methods or ad-hoc solutions.