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A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends)

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

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What is 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 achieved 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 another backend store driver if needed
  • Integration with Flink/Spark/HDFS, and friendly to connect other big data platforms

Quick Start

1. Docker Way (Convenient for Test)

We can use docker run -itd --name=graph -p 8080:8080 hugegraph/hugegraph to quickly start an inner HugeGraph server with RocksDB (in backgrounds) for test/dev. You can visit doc page or the README for more details. (Docker Compose)

Note:

  1. The docker image of hugegraph is a convenience release, but not official distribution artifacts. You can find more details from ASF Release Distribution Policy.

  2. Recommend to use release tag(like 1.2.0) for the stable version. Use latest tag to experience the newest functions in development.

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 tools loader/dashboard/tool/client)
  2. hugegraph-computer (integrated graph computing system)
  3. hugegraph-commons (common & rpc libs)
  4. hugegraph-website (doc & website code)
  5. hugegraph-ai (integrated Graph AI/LLM/KG system)

License

HugeGraph is licensed under Apache 2.0 License.

Contributing

  • Welcome to contribute to HugeGraph, please see How to Contribute & Guidelines for more information.
  • Note: It's recommended to use GitHub Desktop to greatly simplify the PR and commit process.
  • Thank you to all the people who already contributed to HugeGraph!

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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.

Contact Us

  • GitHub Issues: Feedback on usage issues and functional requirements (quick response)
  • Feedback Email: [email protected] (subscriber only)
  • WeChat public account: Apache HugeGraph, welcome to scan this QR code to follow us.

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A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends)

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