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ArcadeData/arcadedb

by Various

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. Arc

A

MCP

ArcadeData/arcadedb

Added 1 June 2026

#arcadedb #database #dbms #distributed #docker #document #embedded #graph

Overview

ArcadeDB is a multi-model database management system that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB, and Redis APIs. It is a conceptual fork of OrientDB and includes support for vector embeddings. The database is written in Java and is available as open source on GitHub.

Best for

Best for
Developers who need a flexible multi-model database with vector capabilities and want to avoid managing separate systems

Use cases

  • Build applications that require graph, document, and key-value models in a single database
  • Use as a vector database for similarity search and AI workflows
  • Migrate from OrientDB to a maintained fork with extended features

Notes

ArcadeDB is a multi-model database management system that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB, and Redis APIs. It is a conceptual fork of OrientDB and includes support for vector embeddings. The database is written in Java and is available as open source on GitHub.

909 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

  • Build applications that require graph, document, and key-value models in a single database
  • Use as a vector database for similarity search and AI workflows
  • Migrate from OrientDB to a maintained fork with extended features

Pros

  • Supports multiple query languages and APIs, reducing integration complexity
  • Includes native vector embedding support for modern AI use cases
  • Open source with an active GitHub repository

Cons

  • Smaller community and ecosystem compared to established databases like PostgreSQL or MongoDB
  • Java runtime dependency may not suit all deployment environments
  • As a fork, documentation and third-party tooling may be less mature

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Supports multiple query languages and APIs, reducing integration complexity
  • Includes native vector embedding support for modern AI use cases
  • Open source with an active GitHub repository

Cons

  • Smaller community and ecosystem compared to established databases like PostgreSQL or MongoDB
  • Java runtime dependency may not suit all deployment environments
  • As a fork, documentation and third-party tooling may be less mature