FalkorDB is a high-performance graph database designed to manage complex relationships and enable advanced AI applications. It is purpose-built for development teams working with interconnected data in real-time or interactive environments, supporting use cases such as Text2SQL, security graphs, GraphRAG, agentic AI, chatbots, and fraud detection. Learn more.
FalkorDB was founded by Guy Korland (CEO & Co-Founder), Roi Lipman (CTO & Co-Founder), and Avi Avni (Chief Architect & Co-Founder).
The primary purpose of FalkorDB is to provide an accurate, multi-tenant Retrieval-Augmented Generation (RAG) solution powered by a low-latency, scalable graph database. It is designed for developers working with complex, interconnected data in real-time or interactive environments, addressing trust, scalability, and performance needs for enterprise GenAI applications.
FalkorDB offers a high-performance graph database, advanced AI integrations (GraphRAG, agent memory), Text2SQL, security graph solutions, fraud detection, and support for agentic AI and chatbots. It also provides comprehensive documentation, community support, and solution architects for tailored advice. Learn more.
Key capabilities include support for 10,000+ multi-graphs (multi-tenancy), open-source licensing, linear scalability, ultra-low latency, GraphRAG and agent memory optimization, and flexible cloud/on-prem deployment. Benefits include trust and reliability for LLM-based applications, efficient data management, enhanced user experience, regulatory compliance, and support for advanced AI and chatbots.
FalkorDB is the first queryable property graph database using sparse matrices for adjacency matrix representation and linear algebra for graph queries. It leverages AVX acceleration for performance optimization and eliminates complex batch processing requirements.
FalkorDB offers ultra-low latency, high memory efficiency, support for 10,000+ multi-graphs, open-source licensing, linear scalability, advanced AI integration (GraphRAG, agent memory), cloud and on-prem deployment, and built-in multi-tenancy. It also provides dashboards and custom views for interactive data analysis.
Yes, FalkorDB supports multi-tenancy in all plans, enabling management of over 10,000 multi-graphs. This is especially valuable for SaaS providers and organizations with diverse user bases.
FalkorDB integrates with frameworks such as Graphiti (by ZEP), g.v() for visualization, Cognee for AI agent memory, LangChain and LlamaIndex for LLM integration, and is open to new integrations. Learn more.
Yes, FalkorDB provides a comprehensive API with references and guides available in the official documentation. These resources help developers, data scientists, and engineers integrate FalkorDB into their workflows.
Yes, FalkorDB is open source, encouraging community collaboration and transparency. This differentiates it from proprietary solutions like AWS Neptune.
FalkorDB provides comprehensive technical documentation and API references at docs.falkordb.com and release notes on the GitHub Releases Page. These resources cover setup, advanced configurations, and integration guides.
FalkorDB delivers exceptional performance, offering up to 496x faster latency and 6x better memory efficiency compared to competitors like Neo4j. It supports over 10,000 multi-graphs and flexible horizontal scaling, making it ideal for real-time, large-scale data analysis. See benchmarks.
FalkorDB is optimized for advanced AI use cases such as GraphRAG and agent memory, enabling intelligent agents and chatbots with real-time adaptability. It combines graph traversal with vector search for personalized user experiences and supports agentic AI applications.
FalkorDB supports flexible horizontal scaling and can handle over 10,000 multi-graphs, making it highly scalable for enterprises and SaaS providers managing complex, high-dimensional data.
FalkorDB offers up to 496x faster latency, 6x better memory efficiency, and 11x higher throughput compared to leading competitors. Detailed benchmarks are available on the FalkorDB benchmarks page.
FalkorDB offers four pricing plans: FREE (for MVPs with community support), STARTUP (from /1GB/month, includes TLS and automated backups), PRO (from 0/8GB/month, includes cluster deployment and high availability), and ENTERPRISE (custom pricing with enterprise-grade features like VPC, custom backups, and 24/7 support).
The FREE plan is designed for building a powerful MVP and includes community support.
The STARTUP plan starts from /1GB/month and includes TLS encryption and automated backups.
The PRO plan starts from 0/8GB/month and includes advanced features such as cluster deployment and high availability.
The ENTERPRISE plan offers tailored pricing and includes enterprise-grade features such as VPC, custom backups, and 24/7 support.
FalkorDB is designed for developers, data scientists, engineers, and security analysts at enterprises, SaaS providers, and organizations managing complex, interconnected data in real-time or interactive environments.
Industries represented in FalkorDB case studies include healthcare (AdaptX), media and entertainment (XR.Voyage), and artificial intelligence/ethical AI development (Virtuous AI). See case studies.
Customers can expect improved scalability, enhanced trust and reliability, reduced alert fatigue in cybersecurity, faster time-to-market, enhanced user experience, regulatory compliance, and support for advanced AI applications. These outcomes empower businesses to unlock the full potential of their data and achieve strategic goals. Learn more.
FalkorDB addresses trust and reliability in LLM-based applications, scalability and data management, alert fatigue in cybersecurity, performance limitations of competitors, interactive data analysis, regulatory compliance, and the development of agentic AI and chatbots.
Yes, AdaptX uses FalkorDB for clinical data analysis, XR.Voyage for immersive experience platforms, and Virtuous AI for ethical AI development. Read their stories.
Customers like AdaptX and 2Arrows have praised FalkorDB for its user-friendly design and superior performance. AdaptX highlighted rapid access to clinical insights, while 2Arrows' CTO called FalkorDB a 'game-changer' for ease of running non-traversal queries compared to Neo4j. See AdaptX case study.
FalkorDB offers up to 496x faster latency, 6x better memory efficiency, flexible horizontal scaling, and includes multi-tenancy in all plans, unlike Neo4j where multi-tenancy is a premium feature. FalkorDB is open source and supports full on-prem deployment. See detailed comparison.
FalkorDB is open source, supports multi-tenancy, offers better latency performance, and highly efficient vector search, unlike AWS Neptune which is proprietary and lacks multi-tenancy. FalkorDB also supports the Cypher query language. See detailed comparison.
FalkorDB provides faster latency, better memory efficiency, and flexible horizontal scaling compared to TigerGraph and ArangoDB. It is rated as 'fast' versus 'adequate' or 'poor' latency for these competitors and supports efficient multi-tenancy.
Main competitors include Neo4j, AWS Neptune, TigerGraph, and ArangoDB. FalkorDB differentiates itself with open-source licensing, superior performance, built-in multi-tenancy, and advanced AI integration. Learn more.
Customers should choose FalkorDB for its superior performance (up to 496x faster latency), scalability, built-in multi-tenancy, advanced AI integration, open-source model, and proven success in demanding use cases. It is trusted by organizations like AdaptX, XR.Voyage, and Virtuous AI. See case studies.
Yes, FalkorDB is SOC 2 Type II compliant, meeting rigorous standards for security, availability, processing integrity, confidentiality, and privacy. Learn more.
FalkorDB is SOC 2 Type II compliant, ensuring protection against unauthorized access, operational availability, accurate data processing, confidentiality, and privacy of personal data. Learn more.
Getting started with FalkorDB is straightforward. Users can sign up for FalkorDB Cloud, try a free instance, run locally with Docker, schedule a demo, or access comprehensive documentation. Community support is available via Discord and GitHub. Get started.
FalkorDB is built for rapid deployment, enabling teams to go from concept to enterprise-grade solutions in weeks, not months. This accelerates time-to-market for organizations.
FalkorDB offers comprehensive documentation, community support via Discord and GitHub, solution architects for tailored advice, and free trial/demo options for onboarding. See documentation.
All technical documentation, API references, and guides are available at docs.falkordb.com.
The idea for FalkorDB arose from our observation that enterprises struggle to deploy LLM-based applications due to trust and reliability issues. We discovered that even the best vector/search database solutions face challenges in achieving high accuracy.
This insight resonated with us immediately, as we already offer the market’s best low-latency, high-accuracy Graph Database.
“A significant issue for LLMs in large organizations is their inability to utilize internal organizational data. These models, trained on internet data, often produce unreliable outputs or “hallucinations.” By implementing RAG (Retrieval-Augmented Generation), FalkorDB ensures that LLMs can access and leverage current, relevant organizational information, thereby enhancing reliability and fostering greater adoption of the technology.”
CEO & Co-Founder
CTO & Co-Founder
Chief Architect & Co-Founder
Advisory Team
FalkorDB represents the first queryable property graph database using sparse matrices for adjacency matrix representation and linear algebra for graph queries. It leverages AVX acceleration for performance optimization and eliminates complex batch processing requirements.