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Vector DBFreemiumOpen Source
DGRAPH
High-performance graph database with vector search for real-time GraphRAG
Apache-2.0
ABOUT
Real-time AI applications need low-latency graph queries combined with vector similarity search, but most graph databases either lack vector support or are not designed for high-throughput production workloads. Dgraph solves this with a distributed graph database that natively indexes and searches vector embeddings alongside graph relationships, delivering millisecond-latency queries for GraphRAG and knowledge graph-powered AI at scale.
INSTALL
docker run -p 8080:8080 -p 9080:9080 dgraph/standalone:latestINTEGRATION GUIDE
1. Build a real-time GraphRAG system that queries both graph relationships and vector similarity in milliseconds
2. Create a knowledge graph for AI agents with native support for semantic search over entity embeddings
3. Implement a fraud detection platform analyzing relationship patterns and entity similarity simultaneously
4. Power a recommendation engine using GraphQL queries that mix graph traversal with vector search results
5. Develop a social network analysis tool that combines connection graphs with content-based semantic search
TAGS
graph-databasedistributedgraphqlvector-searchgraph-ragknowledge-graphreal-timedocker