Multi-tenant graph database for LLMs, offering low-latency, efficient GraphRAG, and clustering on GCP/AWS. Built on RedisGraph, supports OpenCypher for cost-effective, familiar development.
Make your AI reliable with FalkorDB.
docker run -p 6379:6379 -p 3000:3000 -it --rm falkordb/falkordb:edge
Download Docker here
FalkorDB is the first queryable Property Graph database to use sparse matrices to represent the adjacency matrix in graphs and linear algebra to query the graph. It leverages AVX (Advanced Vector Extensions) to accelerate performance and eliminating the need for complex batch processing jobs.
Engage with our community on GitHub for feedback and collaboration opportunities. Our comprehensive documentation covers everything from basic setup to advanced configurations, ensuring a smooth integration with your existing data architecture.
FalkorDB is built on RedisGraph’s robust foundation of linear algebra and sparse matrix libraries. With support for OpenCypher, developers can use familiar syntax while benefiting from advanced clustering and multi-tenant architecture for better resource utilization and cost-efficiency.
Simplifies creating GraphRAG systems, integrates with FalkorDB and LLMs like GPT and Gemini, and aids in building knowledge graphs and querying with Cypher.
Visualizes and manages graph data in FalkorDB, allowing users to navigate nodes and edges interactively, ideal for understanding and monitoring data changes.
Turns a codebase into a knowledge graph, visualizing relationships between entities like classes and functions, helping analyze dependencies, detect bottlenecks, and optimize projects.
