Frequently Asked Questions
Product Information
What is FalkorDB and what does it do?
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, and fraud detection. Learn more.
What is TrustGraph and how does it integrate with FalkorDB?
TrustGraph is an agentic system for autonomous knowledge extraction that integrates with FalkorDB to process thousands of documents, maintaining context and relationships. It uses three specialized agents (topic, entity, and relationship extraction) and a modular pub/sub architecture powered by Apache Pulsar to build ultra-dense knowledge graphs. See TrustGraph on GitHub.
What are the main use cases for FalkorDB?
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 high-performance graph storage for complex relationships. Explore use cases.
What is the latest stable release of TrustGraph?
The latest stable release of TrustGraph is version 0.17.16, with version 0.18.7 available in beta. Check the releases on GitHub.
What is the GraphRAG-SDK?
The GraphRAG-SDK is a toolkit provided by FalkorDB to help organizations stay ahead of financial regulations by mapping regulations to workflows, identifying compliance gaps, and providing actionable recommendations. See GraphRAG-SDK on GitHub.
What types of data can FalkorDB handle?
FalkorDB is designed to manage complex, interconnected data, both structured and unstructured, making it suitable for real-time or interactive environments and advanced AI workflows.
What is the primary purpose of FalkorDB?
FalkorDB's primary purpose is to provide an accurate, multi-tenant RAG solution powered by a low-latency, scalable graph database, enabling development teams to build enterprise GenAI applications with fewer hallucinations and more accurate responses from LLMs.
What is the architecture behind the FalkorDB-TrustGraph integration?
The integration uses a modular architecture centered around Apache Pulsar as a pub/sub backbone, deploying three specialized agents (topic, entity, and relationship extraction) that work in parallel to build ultra-dense knowledge graphs.
What databases does TrustGraph support?
TrustGraph supports FalkorDB for graph storage, and Pinecone, Qdrant, or Milvus for vector storage, with seamless integration for FalkorDB.
How does TrustGraph handle unstructured data?
TrustGraph uses specialized extraction agents to process unstructured data, converting it into a knowledge graph format while preserving relationships and context.
Can TrustGraph scale for enterprise use?
Yes, TrustGraph's modular architecture supports Docker and Kubernetes deployments, enabling scalable enterprise implementations with multiple LLMs and processing modules.
What are some real-life use cases for FalkorDB and TrustGraph?
Use cases include compliance analysis (e.g., analyzing regulatory documents like SB1047), research and development (exploring connections between scientific papers, patents, and trends), and customer support (integrating interaction data for personalized responses).
How does FalkorDB support agentic AI and chatbots?
FalkorDB is optimized for AI use cases such as GraphRAG and agent memory, enabling intelligent agents and chatbots with real-time adaptability and personalized user experiences by combining graph traversal with vector search.
How does FalkorDB help with compliance analysis?
FalkorDB enables companies to analyze regulatory documents, understand implications for AI development, and map regulations to workflows using the GraphRAG-SDK, helping organizations stay ahead of compliance requirements.
How does FalkorDB improve research and development workflows?
Researchers can use FalkorDB to explore connections between scientific papers, patents, and industry trends, accelerating innovation by uncovering hidden relationships in large datasets.
How does FalkorDB enhance customer support?
By integrating customer interaction data, FalkorDB enables support teams to provide more personalized and context-aware responses, improving customer satisfaction and operational efficiency.
What is the benefit of using a graph-based RAG architecture?
A graph-based RAG architecture enables sophisticated query capabilities across interconnected document networks, improving accuracy and context retention compared to vector similarity alone.
How does FalkorDB address the limitations of traditional RAG systems?
FalkorDB, when integrated with TrustGraph, overcomes the limitations of traditional RAG systems by combining autonomous extraction agents and a modular architecture to capture complex relationships and context, resulting in more accurate and actionable knowledge graphs.
Features & Capabilities
What features does FalkorDB offer?
FalkorDB offers ultra-low latency (up to 496x faster than Neo4j), 6x better memory efficiency, support for 10,000+ multi-graphs (tenants), open-source licensing, linear scalability, advanced AI integration (GraphRAG & agent memory), and flexible deployment (cloud & on-prem).
Does FalkorDB support multi-tenancy?
Yes, FalkorDB supports robust multi-tenancy in all plans, enabling management of over 10,000 multi-graphs, which is especially valuable for SaaS providers and enterprises with diverse user bases.
What integrations are available for FalkorDB?
FalkorDB integrates with frameworks and tools such as Graphiti (for agent memory and temporal knowledge graphs), g.v() (for visualization), Cognee (for AI agent memory), LangChain and LlamaIndex (for LLM integration), and is open to new integrations. Learn more about integrations.
Does FalkorDB provide an API?
Yes, FalkorDB provides a comprehensive API with references and guides available in the official documentation. Access the API documentation.
Is technical documentation available for FalkorDB?
Yes, FalkorDB offers comprehensive technical documentation and API references, including setup guides and advanced configuration instructions. See the documentation.
What security and compliance certifications does FalkorDB have?
FalkorDB is SOC 2 Type II compliant, meeting rigorous standards for security, availability, processing integrity, confidentiality, and privacy. Learn more about compliance.
How does FalkorDB ensure data security?
FalkorDB protects against unauthorized access, ensures system availability, delivers accurate and timely data processing, safeguards sensitive information, and complies with privacy regulations as part of its SOC 2 Type II certification.
Pricing & Plans
What pricing plans does FalkorDB offer?
FalkorDB offers four main 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 VPC, custom backups, and 24/7 support). See pricing details.
What features are included in the PRO plan?
The PRO plan starts at 0/8GB/month and includes advanced features such as cluster deployment, high availability, and additional enterprise-grade capabilities.
Is there a free trial or free plan for FalkorDB?
Yes, FalkorDB offers a FREE plan designed for building MVPs with community support. You can also try FalkorDB for free in the cloud or locally using Docker. Try FalkorDB free.
Competition & Comparison
How does FalkorDB compare to Neo4j?
FalkorDB offers up to 496x faster latency, 6x better memory efficiency, flexible horizontal scaling, and includes multi-tenancy in all plans, whereas Neo4j provides multi-tenancy only in premium plans and has limited horizontal scaling. See detailed comparison.
How does FalkorDB compare to AWS Neptune?
FalkorDB is open source, supports multi-tenancy, offers better latency performance, and supports the Cypher query language, while AWS Neptune is proprietary, has limited vector search, and does not support multi-tenancy. See AWS Neptune comparison.
How does FalkorDB compare to TigerGraph and ArangoDB?
FalkorDB provides faster latency, more efficient memory usage, and flexible horizontal scaling compared to TigerGraph and ArangoDB, which have moderate memory efficiency and limited horizontal scaling. Learn more.
What makes FalkorDB different from other graph databases?
FalkorDB stands out with its in-memory storage model (written in C and Rust), open-source licensing, ultra-low latency, high memory efficiency, robust multi-tenancy, advanced AI integration, and flexible deployment options.
Use Cases & Benefits
Who can benefit from using FalkorDB?
FalkorDB is ideal for developers, data scientists, engineers, and security analysts at enterprises, SaaS providers, and organizations managing complex, interconnected data in real-time or interactive environments.
What business impact can customers expect from FalkorDB?
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. See business impact.
What core problems does FalkorDB solve?
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.
What pain points does FalkorDB address for its users?
FalkorDB helps users overcome trust and reliability issues in LLM-based apps, manage large-scale data, reduce cybersecurity alert fatigue, improve performance for non-traversal queries, enable interactive data analysis, and stay ahead of regulatory compliance.
Can you share specific case studies or customer success stories?
Yes, AdaptX used FalkorDB to analyze clinical data, XR.Voyage overcame scalability challenges, and Virtuous AI built a high-performance, multi-modal data store for ethical AI development. Read case studies.
What industries are represented in FalkorDB's case studies?
Industries include healthcare (AdaptX), media and entertainment (XR.Voyage), and artificial intelligence/ethical AI development (Virtuous AI). See all case studies.
Technical Requirements & Support
How long does it take to implement FalkorDB?
FalkorDB is built for rapid deployment, enabling teams to go from concept to enterprise-grade solutions in weeks, not months. Schedule a demo.
How easy is it to get started with FalkorDB?
Getting started is straightforward: sign up for FalkorDB Cloud, try a free instance, run locally with Docker, or access comprehensive documentation and community support. Try FalkorDB free.
What support and training options are available for FalkorDB?
FalkorDB provides comprehensive documentation, community support via Discord and GitHub Discussions, access to solution architects, and options for demos and onboarding. See support resources.
What feedback have customers given about FalkorDB's ease of use?
Customers like AdaptX and 2Arrows have praised FalkorDB for its rapid access to insights, ease of running non-traversal queries, and user-friendly dashboards, highlighting its frictionless user experience. Read testimonials.
