Ross ROSS = Recommend OSS · open-source software intelligence for agents

apache/gravitino

World's most powerful open data catalog for building a high-performance, geo-distributed and federated metadata lake. observed · 2026-08-28

github.com/apache/gravitino · homepage · Java · Apache-2.0 (permissive) 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

Full methodology

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

Member repositories

RepositoryRoleHealth v2
apache/gravitinomain89

For agents

markdown · JSON · MCP: product_card(name="apache/gravitino")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem