A graph database that supports more than 10 billion data, high performance and scalability

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Apache HugeGraph

HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin(a powerful graph traversal language).

Features

• Compliance to Apache TinkerPop 3, support Gremlin & Cypher language
• Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel
• Multi-type Indexes, supporting exact query, range query and complex conditions combination query
• Plug-in Backend Store Driver Framework, support RocksDB, Cassandra, HBase, ScyllaDB, and MySQL/Postgre now and easy to add other backend store driver if needed
• Integration with Flink/Spark/HDFS, and friendly to connect other big data platforms

Quick Start

1. Docker Way

We can use docker run -itd --name=graph -p 8080:8080 hugegraph/hugegraph to quickly start an inner HugeGraph server with RocksDB in background.

Optional: use docker exec -it graph bash to enter the container to do some operations.

2. Download Way

Visit Download Page and refer the doc to download the latest release package and start the server.

3. Source Building Way

Visit Source Building Page and follow the steps to build the source code and start the server.

The project doc page contains more information on HugeGraph and provides detailed documentation for users. (Structure / Usage / API / Configs...)

And here are links of other HugeGraph component/repositories:

1. hugegraph-toolchain (graph loader/dashboard/tool/client)
2. hugegraph-computer (matched graph computing system)
3. hugegraph-commons (common & rpc module)
4. hugegraph-website (doc & website code)

Contributing

Welcome to contribute to HugeGraph, please see How to Contribute for more information.

License

HugeGraph is licensed under Apache 2.0 License.

Thanks

HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax. Thanks to TinkerPop, thanks to Titan, thanks to DataStax. Thanks to all other organizations or authors who contributed to the project.

You are welcome to contribute to HugeGraph, and we are looking forward to working with you to build an excellent open source community.