IRLFirst physical meetup — Bengaluru, Sat May 23, 4PM · RSVP on Luma
HomeToolsMCPHow It WorksStoriesPhilosophyCommunityArchitectureStar on GitHub
All Tools
F
RAGFreeOpen Source

FALKORDB

Ultra-fast graph database for AI knowledge graphs and agent memory

SSPL-1.0
Visit WebsiteGitHubDocs

ABOUT

Building knowledge graphs for AI applications — especially for RAG, agent memory, and multi-hop reasoning — requires a database that can traverse complex relationships at millisecond latency. Traditional graph databases weren't designed for AI workloads, and vector databases lack relational reasoning. FalkorDB bridges this gap with a purpose-built graph database that natively supports Cypher queries, vector similarity search, and real-time traversals in a single system. It runs in-memory for sub-millisecond query performance and supports multi-tenancy for serving multiple AI agents or tenants from a single instance. This makes it ideal for agentic memory systems that need to store, update, and query structured knowledge at inference time.

INSTALL
docker run -p 6379:6379 falkordb/falkordb:latest

INTEGRATION GUIDE

1. Build a persistent knowledge graph for an AI agent that remembers entities and relationships across sessions 2. Power a multi-hop RAG pipeline that traverses relationships between documents, entities, and facts 3. Store and query agentic memory with temporal awareness for long-running autonomous agents 4. Run graph-based retrieval augmented generation over structured enterprise knowledge 5. Detect fraud or security threats by traversing relationship patterns in real-time financial data

TAGS

graph-databaseknowledge-graphragagent-memorycyphervector-searchgen-aiin-memory
Browse all tools