HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges
Graph, millisecond-level OLTP query capability, and large-scale distributed
graph processing (OLAP). The main scenarios of HugeGraph include
correlation search, fraud detection, and knowledge graph.
Convenient
Not only supports Gremlin graph query language and RESTful API but also provides commonly used graph algorithm APIs. To help users easily implement various queries and analyses, HugeGraph has a full range of accessory tools, such as supporting distributed storage, data replication, scaling horizontally, and supports many built-in backends of storage engines.
Efficient
Has been deeply optimized in graph storage and graph computation. It provides multiple batch import tools that can easily complete the fast-import of tens of billions of data, achieves millisecond-level response for graph retrieval through ameliorated queries, and supports concurrent online and real-time operations for thousands of users.
Adaptable
Adapts to the Apache Gremlin standard graph query language and the Property Graph standard modeling method, and both support graph-based OLTP and OLAP schemes. Furthermore, HugeGraph can be integrated with Hadoop and Spark’s big data platforms, and easily extend the back-end storage engine through plug-ins.
The first graph database project in Apache
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