Apache HugeGraph vs GraphDB
Apache HugeGraph
hugegraph.apache.org
GraphDB
graphdb.ontotext.comSide by side
| Figure | Apache HugeGraph | GraphDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · Graph Databases | 8.7 (#5) | 8.1 (#13) |
| AI features | HugeGraph-AI provides Python clients, graph machine learning tools, and LLM tools for knowledge graph construction and GraphRAG applications. | The product page describes native GraphRAG and LangChain integration. |
| Deployment | The Server can be deployed with Docker, a binary archive, a source build, or a legacy one-click deployment tool. | GraphDB can run as a desktop or standalone server application and is also available on AWS and Azure. |
| Product | Apache HugeGraph is a graph system covering graph database, graph computing, and graph AI. | GraphDB is an RDF and SPARQL semantic graph database used for storage and inferencing in the Graphwise AI Platform. |
| 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. | GraphDB documents role and access controls, local, LDAP and OAuth user databases, Basic, GDB, OpenID and Kerberos authentication, SSL/TLS encryption in transit, and security auditing. |
| Support | The project directs users to its Apache community, GitHub issues and discussions, developer mailing list, and Slack channel. | The edition comparison lists community support for Free and SLA support for Enterprise. |
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.
GraphDB
GraphDB is an RDF and SPARQL semantic graph database for storing data and performing inferencing in the Graphwise AI Platform. It supports SPARQL 1.1, RDF4J compatibility, RDFS and OWL 2 RL and QL rulesets, federated queries, and RDF-star. Its real-time forward-chaining reasoning operates across datasets, and the product page describes native GraphRAG and LangChain integration. GraphDB can run as a desktop or standalone server application, be self-hosted, or be deployed on AWS and Azure; downloads are listed for Windows, macOS, Linux, and a platform-independent distribution. The Free edition includes a Lucene connector, one parallel query, and up to five repositories; GraphDB 11 and later requires a free license. Enterprise supports multiple cores, unlimited repositories, high-availability clustering, and connectors for Elasticsearch, OpenSearch, Solr, and Kafka. Free is on-premise only with community support. Enterprise includes SLA support and is licensed per server CPU core, with each cluster node licensed separately. Free costs nothing; Enterprise pricing is on request.