# MarquezProject/marquez

Collect, aggregate, and visualize a data ecosystem's metadata

Repository: https://github.com/MarquezProject/marquez
Canonical: https://ross.abutalabs.com/products/marquez
Homepage: https://marquezproject.ai
Language: Java
License: Apache-2.0
License Family: permissive
Topics: data-lineage, data-discovery, data-governance, data-provenance, metadata-service, data-dictionary, marquez, metadata, data-ecosystem-metadata, data-ops
Last push: 2026-08-26T19:51:39+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 2981, "days_push": 7, "days_rel": 678, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2268, forks 408 (observed 2026-08-28T04:06:32.855387+00:00)

## What it is
Marquez is an open-source metadata service for collecting, aggregating, and visualizing a data ecosystem's metadata. It serves as the reference implementation of the OpenLineage specification, providing a REST API, metadata repository, and web UI for dataset lineage and job run tracking.

## Use cases
- track data lineage across pipelines
- visualize dataset dependencies and job graphs
- collect OpenLineage metadata from Airflow, Spark, dbt, and Flink
- audit dataset schema change history
- perform root cause analysis for failed data jobs
- build a data catalog with dataset discovery
- monitor job runtimes and dataset access frequency

## When to choose
- you need centralized lineage tracking across multiple orchestration and processing frameworks
- you want an OpenLineage-compatible metadata backend with a visual lineage UI
- you need provenance and schema history for data governance or auditing
- you run heterogeneous data pipelines and need upstream/downstream dependency visibility

## When to avoid
- you need a full-featured commercial data catalog with access controls and glossary management
- your stack is a single tool with built-in lineage
- you want a lightweight embedded library rather than a deployed service
- you need column-level lineage out of the box without additional integrations

## Facets
- artifact type: service
- maturity: active
- function: search-engine, data-science, monitoring, api-framework, web-framework, analytics
- domain: databases, analytics, big-data, data-science, self-hosted, apis, developer-tools
- platform: self-hosted, jvm, windows
- tags: data-lineage, metadata-management, openlineage, data-governance, data-catalog, data-provenance, data-discovery, lineage-graph, data-observability, data-engineering, docker, web-server, linux, macos

## Member repositories
- MarquezProject/marquez (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:32.855387+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:42:01.326892+00:00, confidence not recorded.
  - readme: https://github.com/MarquezProject/marquez (fetched 2026-08-28T04:06:32.855387+00:00, sha 0f619c923f82)
  - homepage: https://marquezproject.ai (fetched 2026-08-29T10:22:25.968915+00:00, sha 893a668c9e5b)
  - site_page: https://marquezproject.ai/about (fetched 2026-08-29T10:22:25.971568+00:00, sha 21d6ee91bad4)
  - site_page: https://marquezproject.ai/docs/quickstart (fetched 2026-08-29T10:22:25.973685+00:00, sha e00a7420ad29)
- Data as of 2026-08-30T08:39:29.467469+00:00.