We built Text-to-Cypher to let you chat with FalkorDB graphs using plain English. Get instant Cypher query generation via REST API or MCP server. Open source, Docker-ready, with real-time SSE updates.
As a Cloud Security vendor, you’re building protection systems for environments that constantly change. Your customers deploy across containers, serverless, ephemeral compute, and IaC pipelines. You need to correlate misconfigurations, permissions, and runtime signals across identity, network, and workload layers, at scale, in real time, without losing performance or exceeding the scoped operational costs. That’s where graphs come in.
FalkorDB BYOC deployment now spans AWS and Google Cloud Platform. Run fully managed graph database instances directly within your cloud subscription while maintaining data sovereignty across all major cloud providers.
MCP simplifies how LLMs access tools and graph databases. Learn how FalkorDB’s MCP server enables structured, scalable AI integrations.
A developer-focused guide to understanding and using knowledge graphs for GraphRAG, LLM integration, schema design, and high-precision retrieval in 2025.
Accurate data retrieval via GraphRAG boosts inference, reduces hallucinations, and secures personalized memory storage for AI agents.
Understand ACID transactions. Learn how isolation levels impact data consistency in your applications, plus choosing the right model.
Learn about graph clustering algorithms: hierarchical, modularity-based, label propagation, spectral, and edge betweenness. Analyze their strengths, weaknesses, and optimal use cases.
Explore RedisGraph EOL in this dev guide with practical migration steps and technical validation tips for switching to FalkorDB.
FalkorDB’s integration with Cognee empowers developers to build smarter AI systems with improved query precision and reduced hallucinations.
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.
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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.
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