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RyuGraph review

Free#20 of 39 in Graph Databases

A self-hosted embedded graph database for Cypher queries, graph algorithms, and vector search.

6.9/10Editor score
RyuGraph6.9 Visit RyuGraph

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

RyuGraph is an open-source embedded property graph database from Predictable Labs, Inc., designed for analytical queries on large graphs. Developers integrate it in-process within an application instead of relying on a separately managed database server, and can choose on-disk or in-memory operation. It suits teams that want graph queries and vector search embedded in their software, particularly where self-hosting and schema-defined node and relationship tables fit the architecture. The project is available under the MIT license, with client APIs for multiple programming languages.

Its feature set covers more than graph traversal. Cypher is the query language, and the database supports serializable ACID transactions, full-text search, and graph algorithms including PageRank, Louvain, and connected components. A native disk-based HNSW index supports vector similarity search. These capabilities make RyuGraph relevant when an application needs analytical graph operations alongside vector retrieval, rather than a graph store focused only on relationships. Data import and export formats include CSV, Parquet, and JSON; Parquet, Arrow, and DuckDB are also listed as integrations.

The main architectural tradeoff is deployment: RyuGraph is self-hosted and embedded, not a hosted subscription service. That can suit developers who want database functionality within an application, but teams seeking a separately managed cloud database should look elsewhere. Its schema-defined tables and Cypher query model also make it a more specific fit than a general-purpose database layer. Choose RyuGraph when in-process operation, graph algorithms, transactions, and vector search align with the product's needs; choose another option if managed hosting is central.

RyuGraph pros and cons

  • Where it wins
    • Runs in-process, with on-disk and in-memory database modes
    • Combines Cypher queries, serializable ACID transactions, and graph algorithms
    • Includes a disk-based HNSW vector index and similarity search
  • Where it doesn't
    • Deployment is self-hosted rather than hosted
    • Node and relationship tables require a defined schema
    • Its documented query language is Cypher

RyuGraph fact sheet, pricing and score →

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