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arcadedb is a free, open source machine learning infrastructure project written in Java and released under Apache-2.0. It has 1,156 GitHub stars, 143 forks and 167 open issues, and was last pushed 68 minutes ago. On this registry it ranks #66 of 80 tracked projects in Machine Learning Infrastructure, with 5 head-to-head comparisons available.

ArcadeDB

Multi Model DBMS Built for Extreme Performance

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ArcadeDB is a Multi-Model DBMS created by Luca Garulli, the same founder of OrientDB, after SAP's acquisition. Written from scratch with a brand-new engine made of Alien Technology, ArcadeDB is able to crunch millions of records per second on common hardware with minimal resource usage. ArcadeDB reuses OrientDB's SQL engine (heavily modified) and some utility classes. It's written in LLJ: Low Level Java - still Java21+ but only using low level APIs to leverage advanced mechanical sympathy techniques and reduce Garbage Collector pressure. Highly optimized for extreme performance, it runs from a Raspberry Pi to multiple servers on the cloud.

ArcadeDB is fully transactional DBMS with support for ACID transactions, structured and unstructured data, native graph engine (no joins but links between records), full-text indexing, geospatial querying, and advanced security.

ArcadeDB supports the following models:

ArcadeDB understands multiple languages:

ArcadeDB key capabilities:

  • 70+ Built-in Graph Algorithms — Pathfinding, centrality, community detection, link prediction, graph embeddings, and more — all available out of the box
  • Parallel Query Execution — SQL queries leverage multiple CPU cores for faster execution on large datasets
  • Materialized Views — Pre-computed query results stored and automatically maintained
  • MCP Server — Built-in Model Context Protocol server for AI assistant and LLM integration
  • AI Assistant — Integrated AI assistant in Studio (Beta) for query help and database management
  • Geospatial Indexing — Native spatial queries and proximity searches with geo.* SQL functions
  • TimeSeries — Columnar storage with Gorilla/Delta-of-Delta compression, InfluxDB/Prometheus ingestion, PromQL queries, Grafana integration
  • Hash Indexes — Extendible hashing for faster exact-match lookups alongside LSM-Tree indexes

ArcadeDB can be used as:

  • Embedded from any language on top of the Java Virtual Machine
  • Embedded from Python via bindings: arcadedb-embedded-python
  • Remotely by using HTTP/JSON
  • Remotely by using a Postgres driver (ArcadeDB implements Postgres Wire protocol)
  • Remotely by using a Redis driver (only a subset of the operations are implemented)
  • Remotely by using a MongoDB driver (only a subset of the operations are implemented)
  • By AI assistants via the built-in MCP Server (Model Context Protocol)

For more information, see the documentation.

Use Cases

Explore real-world examples in the arcadedb-usecases repository — self-contained projects with Docker Compose, SQL schemas, and runnable demos covering:

  • Recommendation Engine — graph traversal + vector similarity + time-series
  • Knowledge Graphs — co-authorship and citation networks with full-text search
  • Graph RAG — retr

readme truncated — read the full docs on github

Frequently asked questions

Is arcadedb free to use?

arcadedb is open source under the Apache-2.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does arcadedb do?

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 M

What is arcadedb written in?

arcadedb is primarily written in Java. Its source is publicly available at https://github.com/ArcadeData/arcadedb, and it has 1,156 GitHub stars.