Apache HugeGraph vs Eclipse RDF4J
Apache HugeGraph
hugegraph.apache.orgEclipse RDF4J
rdf4j.orgSide by side
| Figure | Apache HugeGraph | Eclipse RDF4J |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Graph Databases | 8.7 (#5) | 8.8 (#4) |
| Integrations | The project documents integration with Spark and SeaTunnel and compatibility with Hadoop and Flink. | Documented compatible systems include GraphDB, Halyard, Stardog, Amazon Neptune, Blazegraph, Oracle RDF, MarkLogic, Strabon and Virtuoso. |
| License | The HugeGraph-AI documentation identifies Apache License 2.0. | The project states that Eclipse RDF4J is licensed under the Eclipse Distribution License version 1.0. |
| Runtime requirement | The download page recommends Java 11 and says Java 11 is required starting with version 1.5.0. | The latest stable release, RDF4J 6.1.0, requires Java 25 or newer. |
| Security | User authentication is disabled by default; the project advises enabling authentication and authorization, maintaining an IP allowlist, and avoiding direct public exposure of query endpoints in production. | The Eclipse project page links to the Eclipse Foundation vulnerability reporting channel. |
| Storage | The Server supports RocksDB as its default standalone backend, HStore for distributed storage, and HBase. | RDF4J includes a transactional in-memory store with optional disk persistence and a transactional Native Store that targets medium-sized datasets around 100 million triples. |
Plans
In their own words
Apache HugeGraph
Apache HugeGraph is an open-source graph system combining a graph database, graph computing, and graph AI. It supports Gremlin and Cypher/OpenCypher queries, a REST API, ACID transactions, graph algorithms, and vector search. HugeGraph-AI adds Python clients, graph machine-learning tools, and LLM tools for knowledge-graph construction and GraphRAG applications. Storage options include RocksDB for standalone use, HStore for distributed storage, and HBase. The project documents integrations with Spark and SeaTunnel and compatibility with Hadoop and Flink. Its toolchain provides graph loading, visualization, backup, restore, and migration; Hubble is a web interface for visualization and management. Documentation covers standalone deployments up to 2 TB and distributed deployments up to 1 PB. The project describes high-speed imports and millisecond-level real-time queries for hundreds of billions of graph data. It runs on Linux and macOS and can be self-hosted. The open-source plan costs nothing. Java 11 is recommended and required from version 1.5.0.
Eclipse RDF4J
Eclipse RDF4J is a modular Java framework for parsing, storing, querying, and reasoning over RDF data. It supports SPARQL 1.1 query and update, and its API can access remote RDF repositories in the same way as local ones. Supported formats include RDF/XML, Turtle, N-Triples, N-Quads, JSON-LD, TriG, and TriX. Storage options include a transactional in-memory store with optional disk persistence and a transactional Native Store aimed at medium-sized datasets around 100 million triples. Extensions add full-text search, RDFS inferencing, rule-based reasoning, SHACL and SPIN validation, and geospatial queries. The SDK bundles libraries, Server, Workbench, Console, and Javadoc API; Workbench includes a web interface with a SPARQL editor. Developers can use Maven artifacts or download an SDK zip or onejar. RDF4J is free under the Eclipse Distribution License, version 1.0. The latest stable release, 6.1.0, requires Java 25 or newer. The project describes its core databases as mainly intended for small to medium-sized datasets and notes third-party stores may scale further or offer additional features.