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Vector DBFreemiumOpen Source
NEBULAGRAPH
Distributed graph database with vector search for GraphRAG at scale
Apache-2.0
ABOUT
Traditional vector databases treat all data points as independent vectors, losing the rich relationships between entities in AI applications. NebulaGraph solves this by combining a distributed graph database with vector search, enabling GraphRAG architectures that traverse both semantic similarity and graph relationships at scale across billions of nodes and edges.
INSTALL
docker run -it vesoft/nebula-graphINTEGRATION GUIDE
1. Build a large-scale GraphRAG system that traverses entity relationships across billions of nodes
2. Implement a fraud detection pipeline that analyzes transaction graphs alongside semantic entity similarity
3. Power a recommendation engine combining collaborative filtering with graph traversal and vector embeddings
4. Create a knowledge graph memory layer for LLM agents that supports both relationship and similarity queries
5. Build an enterprise knowledge management system with distributed graph storage and semantic search
TAGS
graph-databasedistributedvector-searchgraph-ragknowledge-graphnGQLdocker