What Apache Gravitino does

Apache Gravitino is an Apache Software Foundation Top-Level Project providing a high-performance, geo-distributed, federated metadata lake for unified management of data and AI assets across heterogeneous sources. The platform, written in Java and requiring JDK 17, exposes REST APIs and Java/Python SDKs, with connectors spanning 15+ systems: relational databases (MySQL, PostgreSQL, Doris, StarRocks, ClickHouse, Hologres, OceanBase), lakehouse formats (Apache Iceberg, Apache Hudi, Apache Paimon, Delta Lake), messaging (Apache Kafka), filesets (HDFS, S3, GCS, OSS), and AI/ML assets (models, features, vector data). Its distinguishing technical architecture is direct, bidirectional metadata management—changes in Gravitino propagate to underlying systems and vice versa—contrasted with traditional passive collection. Additional capabilities include a Model Context Protocol (MCP) server for AI agent integration, a Table Maintenance Service for automated lakehouse optimization, credential vending for secure multi-cloud access, Apache Ranger integration for unified RBAC, and standalone Iceberg REST and Lance REST catalog services.

The project entered the Apache Incubator in June 2024 and graduated to Top-Level Project status on June 3, 2025. Since then it has shipped eight releases through version 1.3.0 (June 2026), with named production adopters including Uber (multi-cloud AI clusters) and Pinterest (Iceberg REST Catalog in production); Datastrato has publicly committed support. As a community-led open-source project distributed under Apache License 2.0, Gravitino has no direct revenue model—commercial adoption occurs through self-hosted enterprise deployments and third-party support providers. The community has grown to 2,600+ GitHub stars (130%+ YoY) and 40+ unique developers per major release, with visitors from 103 countries reaching documentation in the second half of 2024.

Apache Gravitino is governed as an open-source community project under the Apache Software Foundation, a US 501(c)(3) nonprofit, with no parent-company control beyond ASF oversight. Go-to-market is community-led, relying on GitHub, ASF Slack (#gravitino), developer mailing lists, technical documentation, blog posts, and conference appearances at Community Over Code (NA and Asia) and QCon Shanghai. Distribution is frictionless via Apache download mirrors, Docker Hub, GitHub, and versioned Trino connector packages.

Name

Apache Gravitino

Legal name

Apache Gravitino

Website

https://gravitino.apache.org

Company type

Private

Founded year

2024

Operating status

Operating

Short description

Apache Gravitino is an Apache Software Foundation Top-Level Project providing a federated, geo-distributed metadata lake for unified management of data and AI assets across 15+ heterogeneous sources, with native connectors for Trino, Spark, Flink, Iceberg, and vector data.

Ownership category

akta.pro rank

Product category

Metadata Management

NAICS

Computer Systems Design and Related Services (54151), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming, Data Processing, Etc. (7370), Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

Configuration Management Database (CMDB) Platforms (HDAEALAE)

akta.pro secondary industries

Governance, Risk & Compliance (GRC) Platforms (BPAEAPAA), Cloud Compliance, Audit & Continuous Controls Monitoring (CCM/GRC) (HDABAHAI)

Keywords

• Metadata management
• Data catalog
• Lakehouse federation
• Data governance
• Unified metadata

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Operations

Revenue model

1. Open Source Distribution: Apache Gravitino is an open-source project distributed under the Apache License 2.0. There is no direct revenue model; the project is maintained by community contributors and sponsored by the Apache Software Foundation. Commercial adoption occurs through organizations using the open-source software independently or through commercial support providers in the ecosystem.

Go-to-market motion1 record

Distribution channels4 records

Marketing channels6 records

Core offering

Apache Gravitino is a high-performance, geo-distributed, federated metadata lake that provides unified metadata management across heterogeneous data and AI assets — including relational databases, file/HDFS stores, streaming systems, and AI models — accessible from multiple query/compute engines such as Trino, Spark, Flink, and Daft. It also offers standalone REST catalog services (Apache Iceberg REST, Lance REST), a Model Context Protocol (MCP) server, and a Table Maintenance Service for unified governance, access control, and asset management.

Product overview

Apache Gravitino is a unified, federated metadata lake platform for managing data and AI assets across heterogeneous sources. The core Gravitino server (with REST API and Java/Python SDKs) provides unified metadata management, governance, and access control for relational databases, file stores, and event streams. Key products include specialized REST catalog services for Apache Iceberg and Lance (vector data), connectors for Trino/Spark/Flink/Daft query engines, Web UI and CLI management interfaces, and an MCP server for AI agent integration. The platform supports multi-engine access (Spark, Trino, Flink), geo-distributed deployment, credential vending for secure cloud storage access, and metadata-driven automation via statistics, policies, and job systems.

Differentiator

Problem solved

Functional benefit

Products and services

• Apache Gravitino (Core Server) High-performance, geo-distributed, federated metadata lake and unified catalog server that manages metadata for data and AI assets across relational databases, file stores, and streaming systems, with multi-engine access for Trino, Spark, Flink, and Daft.
• Gravitino Iceberg REST Catalog Service Standards-based, Apache Iceberg REST Catalog-compatible service for managing Iceberg tables across engines such as Trino and Spark.
• Gravitino Lance REST Service REST service for cataloging and managing Apache Lance datasets, exposing Lance-format tables to compatible engines.
• Gravitino MCP Server Model Context Protocol server that exposes Gravitino catalog, governance, and AI-asset metadata to LLM-based agents and external tools.
• Gravitino Table Maintenance Service (TMS / Optimizer) Standalone service that runs optimization jobs such as compaction and cleanup on tables registered in Gravitino.

Quantifiable outcome

• 130%+ GitHub star growth year-over-year
• +2 more outcomes

Named customers3 records

Segments3 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration26 records

AI capability4 records

Feature15 records

Partnerships

One partnership is on record.

• Apache Software FoundationflagshipStrategic or Co-development Partner · 3 June 2025Apache Gravitino is an Apache Top-Level Project (TLP) under the Apache Software Foundation. ASF provides governance, infrastructure, licensing (Apache License 2.0), and vendor-neutral oversight. The project entered Apache Incubator in June 2024 and graduated to TLP status on June 3, 2025. ASF provides the Foundation, License, Events, Privacy Policy, Security, Sponsorship, and Thanks infrastructure.

Scale indicators5 records

Recent moves1 record

Expansion highlights7 records

Broad incumbents

• Collibra: Enterprise data intelligence platform with strong governance, lineage, and data quality capabilities. Adjacent competitor to Gravitino for unified data governance workloads in large regulated enterprises.
• Alation: Established enterprise data catalog and governance vendor with deep Fortune 500 penetration. Competes with Gravitino on data discovery and governance, though Gravitino's edge is in lakehouse federation and AI asset management rather than Alation's data stewardship focus.
• AWS Glue Data Catalog: Hyperscaler-native metadata catalog integrated with the broader AWS analytics stack (Athena, EMR, Redshift, Lake Formation). Competes with Gravitino on federated metadata access, especially for AWS-centric enterprises, but lacks Gravitino's multi-engine and multi-cloud federation.

Direct peers

• OpenMetadata: Open-source metadata and governance platform covering data discovery, lineage, and collaboration. Competes with Gravitino for unified metadata management workloads in enterprise data platforms with a similar community-driven model.
• Apache Polaris: Apache Incubator project from Snowflake providing an Iceberg REST catalog. The closest sibling project under ASF, competing with Gravitino's Iceberg REST catalog service for the same open-table-format catalog workload.
• DataHub: Open-source metadata platform originally built at LinkedIn. Directly comparable to Gravitino as a unified data catalog with discovery, lineage, and governance; both pursue open-source, community-led distribution models targeting enterprise data platforms.
• Unity Catalog: Open data catalog from Databricks with native support for Iceberg, Delta, and ML assets. Most direct competitor to Gravitino's federated Iceberg REST catalog and AI asset management capabilities, though backed by Databricks rather than vendor-neutral governance.

Emerging players

• Atlan: Active metadata platform with strong focus on data discovery, governance, and collaboration built atop open standards. Competes for the same enterprise data catalog workload with a more productized, commercial-led approach.
• LakeFS: Open-source data lake version control and management platform. Adjacent to Gravitino's metadata and fileset management, with overlapping concern for managing data across S3/GCS/Azure storage layers in lakehouse architectures.
• Project Nessie: Open-source transactional catalog and data lake version control from the Iceberg community (originally Cloudera). Comparable in scope to Gravitino's Iceberg REST catalog service for federated lakehouse metadata access.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/apache/gravitino

Compliance1 record

Revenue estimate

Valuation estimate

Number of profiles

Profiles6 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Apache Gravitino