HugeGraph is a full-stack graph system covering graph database, graph computing, and graph AI.
It provides complete graph data processing capabilities from storage and real-time querying to offline analysis, and supports both Gremlin and Cypher query languages.
HugeGraph supports high-speed import and millisecond-level real-time queries for up to hundreds of billions of graph data, with deep integration with big data platforms like Spark and Flink, and can use the HugeGraph toolchain for data import, visualization, and operations.
In the AI era, combined with Large Language Models (LLMs), it provides powerful graph computing capabilities for intelligent Q&A, recommendation systems, fraud detection, and knowledge graph applications.
Supports Gremlin graph query language and RESTful API, and provides commonly used graph retrieval interfaces. It includes a complete set of supporting tools with distributed storage, data replication, horizontal scaling, and multiple built-in backend storage engines for efficient query and analysis workflows.
Deeply optimized for graph storage and graph computing, it provides batch import tools to efficiently ingest massive data, achieves millisecond-level graph retrieval latency with optimized queries, and supports concurrent online operations for thousands of users.
Supports the Apache Gremlin standard graph query language and the Property Graph modeling method, with both OLTP and OLAP graph computing scenarios. It can be integrated with Hadoop and Spark and can extend backend storage engines through plug-ins.
Integrates LLM with GraphRAG capabilities, automated knowledge graph construction, and 20+ built-in graph machine learning algorithms to build AI-driven graph applications.
Supports horizontal scaling and distributed deployment, seamlessly migrating from standalone to PB-level clusters, and provides distributed storage engine options for different scale and performance requirements.
Adheres to Apache TinkerPop standards, provides multi-language clients, is compatible with mainstream big data platforms, and is backed by an active and evolving community.
It includes graph loader & dashboard & backup tools
We do a Pull Request contributions workflow on GitHub. New users are always welcome!
Join the ASF Slack channel for community discussions
Could also follow the WeChat account “HugeGraph” for updates