x500 Faster than Neo4j
Multi-tenant graph database for LLMs, offering low-latency, efficient GraphRAG, and clustering on GCP/AWS. Supports OpenCypher for cost-effective, familiar development.
“FalkorDB feeds our foundational model algorithms via PyTorch and Tensorflow dataloaders, and is updated with output embeddings from the aforementioned algorithms as well. This helps power our AI advice solution to help businesses create more powerful and trustworthy applications.”
Chris Patton
Head of Product, Virtuous AI
“AdaptX uses FalkorDB to store high-dimensional data about medical and clinical patient data and results”
Matthew Goos
CTO, AdaptX
“As one of earliest adopters of FalkorDB (since early 2019), we chose to base our foundation on best-suited technology core but equally to be surrounded by the support team that is an absolute pleasure to work with.”
Peter Styk
CEO, XR.VOYAGE
Deploy FalkorDB on the cloud for scalable, high-performance data processing. Get instant access to cloud resources and advanced capabilities to handle complex graph-based AI applications with ease.
To learn more about how to get started see FalkorDB documentation
Easily deploy FalkorDB in any environment with Docker for streamlined setup and management. Perfect for developers who need a flexible, containerized solution that integrates smoothly into existing workflows.
Download Docker here
docker run -p 6379:6379 -p 3000:3000 -it --rm falkordb falkordb:edge
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.
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.
Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
USE CASES
SOLUTIONS
Simply ontology creation, knowledge graph creation, and agent orchestrator
Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
COMPARE
CTO at Intel Ignite Tel-Aviv
I enjoy using FalkorDB in the GraphRAG solution I'm working on.
As a developer, using graphs also gives me better visibility into what the algorithm does, when it fails, and how it could be improved. Doing that with similarity scoring is much less intuitive.
Dec 2, 2024
Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.
RESOURCES
COMMUNITY
