apache/gravitino
World's most powerful open data catalog for building a high-performance, geo-distributed and federated metadata lake. observed · 2026-08-28
Health v2 · maintenance only
89/100
- Activity 99
- Release rhythm 78
- Longevity 87
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 48.5
- age_days: 1229
- days_rel: 65
- days_push: 7
- n_releases_24m: 13
Adoption not part of the score
3188 stars · 916 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Apache Gravitino is a high-performance, geo-distributed, federated metadata lake that provides unified metadata management across diverse data sources such as Hive, MySQL, PostgreSQL, HDFS, and S3. It offers end-to-end data governance including access control, auditing, and discovery, with multi-engine support for query engines like Trino, Spark, and Flink.
Use cases
- unify metadata across hive mysql and s3 in one catalog
- federated metadata discovery across data lakes and clouds
- manage access control and auditing for all data sources
- query lakehouse tables with trino spark or flink without changing sql
- track ai models and features alongside data assets
- share metadata across regions with a geo-distributed deployment
- replace hive metastore with a modern open data catalog
When to choose
- you need a single catalog spanning multiple metadata sources, engines, and clouds
- you want direct metadata management where changes reflect immediately in underlying systems
- you need geo-distributed metadata sharing across regions or cloud providers
- you want unified governance like access control and auditing over data and AI assets
When to avoid
- you only need a simple single-source metastore for one engine
- you require a lightweight embedded catalog with no server component
- your stack is entirely non-JVM and you cannot run a Java 17 service
- you need mature AI asset management today, as it is still work in progress
Facets
service · maturity active
database search-engine auth api-framework middleware databases big-data analytics self-hosted developer-tools jvm self-hosted cloud data-catalog metadata-lake lakehouse federated-metadata data-governance geo-distributed trino spark flink hive-metastore iceberg ai-asset-management data-engineering linux macos docker
3 sources
- readme: https://github.com/apache/gravitino · fetched 2026-08-28 · c0ae95c36640
- homepage: https://gravitino.apache.org · fetched 2026-08-29 · 09fe8bc980f7
- site_page: https://gravitino.apache.org/docs/1.3.0 · fetched 2026-08-29 · 34ca78487350
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| apache/gravitino | main | 89 |
For agents
markdown · JSON · MCP: product_card(name="apache/gravitino")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem