# FalkorDB FalkorDB is a Redis-based graph database for graph analytics, GraphRAG, agent memory, and other applications built on interconnected data. It helps technical teams structure and query relationships for AI applications, chatbots, fraud detection, and security analysis. - Findings24: - Website: - Pricing: Freemium - Categories: AI Knowledge Graph ## What is FalkorDB? FalkorDB is a Redis-based, open-source graph database for applications that depend on interconnected data. It is positioned for GraphRAG, agent memory, graph analytics, chatbots, fraud detection, and security workloads, with support for multiple graphs and tenants. The platform lets teams represent domain entities and their relationships, then query that context for AI and operational applications. Its GraphRAG SDK adds ingestion for structured and unstructured sources, ontology discovery and refinement, knowledge-graph construction, and multi-agent orchestration. Deployment and operational features such as TLS, VPCs, clustering, high availability, automated backups, and enterprise support depend on the selected plan. ## What can FalkorDB do? ### Multi-graph and multi-tenancy Run multiple graphs and tenant workloads on the platform, with graph access control available across the listed plans. This supports applications that keep distinct data domains or customer environments separated. ### GraphRAG knowledge workflows Combine large language models with domain-specific knowledge graphs to support natural-language queries, traceable retrieval logic, relationship-based context, and structured answers. ### Structured and unstructured data ingestion The GraphRAG SDK provides an ETL workflow for sources including PDF, CSV, HTML, TXT, JSON, and URLs, helping teams turn varied source material into graph-based knowledge. ### Ontology discovery and graph construction Generative AI can detect and construct ontologies from datasets. Teams can review, modify, iterate on, and constrain the detected ontology before using it to build a knowledge graph. ### Cypher and graph analysis FalkorDB supports Cypher queries and graph traversal for exploring entities and relationships. These capabilities are used for retrieval, recommendations, anomaly analysis, and investigations. ### Deployment and production controls Plan-dependent operations include TLS, VPC support, clustering, high availability, multi-zone deployment, continuous persistence, automated backups, and enterprise support. The site lists AWS, Azure, and GCP as cloud providers. ## Use Cases ### GraphRAG applications Teams can connect LLMs to structured and unstructured domain knowledge, use ontology-driven graph construction, and retrieve relationship-aware context for more traceable and relevant responses. ### Agentic AI and agent memory Developers can combine graph traversal with vector search to build personalized agentic systems. User profiles, preferences, activities, and persistent context can be connected for adaptive interactions. ### Context-aware chatbots Conversational applications can extract entities, link facts, and map relationships across user, product, and session data to maintain longer-term context and provide real-time recommendations. ### Fraud and AML investigations Financial crime teams can model transactions, accounts, institutions, IPs, and devices to trace fund flows, identify hidden relationships, correlate accounts, and investigate suspicious patterns. ### Security and threat intelligence Security vendors can store findings, vulnerabilities, assets, and related entities in a flexible graph, then query interconnected security domains for near-real-time analysis and threat surfacing. ## Frequently Asked Questions ### What kind of product is FalkorDB? FalkorDB is an open-source, Redis-based graph database focused on graph workloads such as GraphRAG, agent memory, graph analytics, and multi-tenant applications. ### What data can the GraphRAG SDK process? The SDK describes an ETL workflow for structured and unstructured data, including PDF, CSV, HTML, TXT, JSON, and URLs. It can use generative AI to construct knowledge graphs from those sources. ### Does FalkorDB support ontology creation? Yes. The GraphRAG SDK can detect and construct ontologies from datasets, while allowing users to review, modify, iterate on, and constrain the detected ontology. ### Is there a free way to start? Yes. The pricing page lists a free plan for building an MVP, with multi-graph and multi-tenancy and graph access control. TLS, clustering, high availability, backups, and other operational capabilities vary by paid plan. ### Which deployment environments are listed? The site lists AWS, Azure, and GCP as cloud providers. It also describes deployment through cloud infrastructure or containerized environments; specific operational features depend on the plan. ## Quick Facts - **Category**: Graph database and GraphRAG platform - **Underlying technology**: Redis-based, open-source graph database - **Primary users**: Technical teams building AI/ML, GenAI, graph analytics, and multi-tenant applications - **Query language**: Cypher - **GraphRAG SDK inputs**: PDF, CSV, HTML, TXT, JSON, and URLs - **Cloud providers listed**: AWS, Azure, and GCP