FalkorDB is a high-performance graph database designed for managing complex relationships and enabling 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 offers a graph database platform with features for high-performance graph storage, multi-tenancy, advanced AI integration, and real-time analytics. Services include cloud and on-prem deployment, comprehensive documentation, community support, and solution architects for tailored advice. See all offerings.
FalkorDB is used for Text2SQL (natural language to SQL on complex schemas), security graphs (for CNAPP, CSPM & CIEM), GraphRAG (advanced graph-based retrieval), agentic AI and chatbots, fraud detection, and as a high-performance graph database for complex relationships. Explore use cases.
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. Learn more.
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.
The primary purpose of FalkorDB is to provide an accurate, multi-tenant RAG solution powered by a low-latency, scalable graph database technology, enabling enterprise GenAI and advanced AI workflows. Learn more.
FalkorDB enables 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. See business impact.
Notable customers include AdaptX (healthcare analytics), XR.Voyage (media/entertainment), and Virtuous AI (ethical AI development). Read their stories.
Yes. AdaptX used FalkorDB for rapid clinical data analysis, XR.Voyage overcame scalability challenges, and Virtuous AI built a high-performance, multi-modal data store. See all case studies.
FalkorDB is built for rapid deployment, allowing teams to go from concept to enterprise-grade solutions in weeks, not months. Onboarding options include cloud sign-up, free trials, Docker deployment, and comprehensive documentation. Get started.
FalkorDB offers four 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, includes VPC, custom backups, and 24/7 support). See pricing.
The FREE plan is designed for building a powerful MVP and includes community support. See details.
The STARTUP plan starts at /1GB/month and includes TLS and automated backups. See details.
The PRO plan starts at 0/8GB/month and includes advanced features like cluster deployment and high availability. See details.
The ENTERPRISE plan offers tailored pricing and includes enterprise-grade features like VPC, custom backups, and 24/7 support. See details.
Key features 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. See all features.
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. Learn more.
FalkorDB is optimized for 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. See AI features.
FalkorDB integrates with frameworks such as Graphiti (by ZEP), g.v() for visualization, Cognee, LangChain, and LlamaIndex for LLM integration. See integrations.
Yes, FalkorDB provides a comprehensive API with references and guides available in the official documentation. See API docs.
FalkorDB offers comprehensive technical documentation and API references, including setup guides, advanced configurations, and release notes. See documentation.
Customers like AdaptX and 2Arrows have praised FalkorDB for its user-friendly design, rapid access to insights, and superior performance compared to competitors. Read AdaptX's story.
FalkorDB delivers ultra-low latency, linear scalability, open-source transparency, multi-tenancy, advanced AI optimization, and enhanced user experience for interactive data analysis. See all capabilities.
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 agentic AI/chatbot development. See solutions.
FalkorDB offers 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. See benchmarks.
FalkorDB supports flexible horizontal scaling and can handle large-scale, high-dimensional data efficiently, making it ideal for enterprises and SaaS providers. Learn more.
FalkorDB enables fast, interactive analysis of complex data through dashboards and custom views, enhancing user experience for real-time decision-making. See features.
FalkorDB provides 6x better memory efficiency than competitors, allowing efficient handling of large-scale, high-dimensional data and reducing operational costs. See benchmarks.
FalkorDB's ultra-low latency and high throughput make it ideal for real-time applications such as fraud detection, security analytics, and AI-powered chatbots. See use cases.
FalkorDB offers up to 496x faster latency, 6x better memory efficiency, flexible horizontal scaling, and includes multi-tenancy in all plans, unlike Neo4j where it's a premium feature. See detailed comparison.
FalkorDB is open source, supports multi-tenancy, offers better latency performance, and is more memory efficient than AWS Neptune, which is proprietary and lacks multi-tenancy. See detailed comparison.
FalkorDB provides faster latency, more efficient memory usage, and flexible horizontal scaling compared to TigerGraph's adequate latency and limited scaling. See comparison.
FalkorDB demonstrates superior latency and memory efficiency, with flexible horizontal scaling, making it a better choice for performance-critical applications than ArangoDB. See comparison.
FalkorDB stands out for its exceptional performance, scalability, multi-tenancy in all plans, advanced AI integration, open-source licensing, and enhanced user experience. See why customers choose FalkorDB.
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. See compliance details.
Support options include comprehensive documentation, community support via Discord and GitHub, solution architects for tailored advice, and 24/7 support for enterprise customers. See support options.
You can sign up for FalkorDB Cloud, try a free instance, run FalkorDB locally with Docker, schedule a demo, or access documentation and community resources. Get started.
Official documentation, including setup guides and API references, is available at docs.falkordb.com.
You can join the FalkorDB community on Discord or participate in GitHub Discussions for real-time support and collaboration. Join Discord | GitHub Discussions
Some problems announce themselves as graph problems. Most don’t. A scheduler that can’t double-book reviewers, a fraud queue that keeps sending two analysts after the
You have a graph with fifty million nodes representing users, products, transactions, and the invisible threads connecting them all. Someone asks: “Find every user who
FalkorDB adds MaxFlow, Harmonic Centrality, and programmable UDF traversal. These three graph database algorithms expand what you can compute, optimize, and automate directly inside the graph layer.
Securin optimized their AI security agents by migrating from leading graph database provider to FalkorDB, achieving 0.3s latencies on complex 7-hop queries and eliminating a 25% query failure rate.
FalkorDB introduces native array and range indexing for graph databases, enabling O(log n) queries on multivalued properties without schema normalization, delivering 10-100x speedups.
FalkorDB introduces user-defined functions (UDFs) written in JavaScript, allowing developers to extend graph database functionality with custom logic. FLEX library provides pre-built functions for text processing, similarity metrics, and date manipulation.
FalkorDB Browser now supports Personal Access Tokens for secure API authentication. Generate granular, long-lived JWT credentials for automated scripts and CI/CD pipelines using our documented API.
Read about security graphs to model complex cloud relationships between users, roles, policies, and resources. Using FalkorDB, query indirect access chains, enforce least privilege, and detect lateral movement risks in real time for CIEM and threat analysis.
Security teams need real-time attack path discovery across multi-cloud environments. Graph databases process entity relationships for sub-100ms threat analysis.
One of the lesser-known challenges is the memory consumed by storing identical string values over and over again. Think of common attributes like “city,” “category,” or “status” that might appear on thousands, or even millions, of nodes and edges. A powerful solution to this problem is string interning.