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FalkorDB
Ultra-fast, Multi-tenant Graph Database
- Authority
- 48 reach 7 · trust 5 · quality 21 · freshness 15
- Tier
- listed
- llms.txt
- https://www.falkordb.com/llms.txt
- Sections
- 3
- Links
- 184
- Size
- 53706 bytes
- Popularity rank
- #394080
- Categories
- Data and analytics
- For agents
- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-19T10:43:03.295Z
- Last checked
- 2026-10-21T02:16:42.576Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T02:16:37.354Z. Cached copy · Source on falkordb.com
# FalkorDB
> Ultra-fast, Multi-tenant Graph Database
## Posts
- [Why the KPMG AI Report Demands GraphRAG for Enterprise AI](https://www.falkordb.com/blog/kpmg-ai-report-graphrag-ai-agents/): The latest KPMG AI Report highlights data quality and privacy as major roadblocks. Discover why GraphRAG is essential for enterprise AI agents.
- [ACID Transactions: Isolation Levels and Data Consistency](https://www.falkordb.com/blog/glossary/acid-transactions-isolation-data-consistency/): Understand ACID transactions. Learn how isolation levels impact data consistency in your applications, plus choosing the right model.
- [VectorRAG vs GraphRAG: Technical Challenges in Enterprise Generative AI](https://www.falkordb.com/blog/vectorrag-vs-graphrag-technical-challenges-enterprise-ai-march25/): A technical deep-dive comparing VectorRAG vs GraphRAG architectures across 10 critical engineering dimensions, helping AI architects make data-driven decisions for enterprise generative AI implementations.
- [A Guide to Implementing a GraphRAG Workflow Using FalkorDB, LangChain and LangGraph](https://www.falkordb.com/blog/graphrag-workflow-falkordb-langchain/): Discover how to implement GraphRAG using FalkorDB's hybrid query capabilities combined with LangChain and LangGraph to build AI systems that leverage both graph relationships and semantic search.
- [How to Deploy and Use a Graph Database](https://www.falkordb.com/blog/graph-database-deployment-guide/): Learn what a graph database is and how to deploy FalkorDB graph databases on AWS/GCP, run Cypher queries, and benefit from the power of interconnected data.
- [NoSQL Database: Modern Architecture for Scalable Apps](https://www.falkordb.com/blog/nosql-database-modern-architecture-scalability/): NoSQL database architectures overcome relational limitations with schema flexibility and distributed processing. Learn how graph, document, key-value, and columnar NoSQL models power AI and real-time analytics.
- [FalkorDB at NVIDIA GTC 2025: Driving Real-Time Knowledge Graphs for GenAI Applications](https://www.falkordb.com/news-updates/falkordb-nvidia-gtc-2025-real-time-knowledge-graphs/): At Nvidia GTC 2025, FalkorDB presents on real-time knowledge graphs for GenAI. Learn how graph databases enable LLM-enhanced reasoning and fraud detection, solving critical AI challenges.
- [Graph Clustering Algorithms: Usage and Comparison](https://www.falkordb.com/blog/graph-clustering-algorithms-comparison/): Learn about graph clustering algorithms: hierarchical, modularity-based, label propagation, spectral, and edge betweenness. Analyze their strengths, weaknesses, and optimal use cases.
- [Build AI Agents with Memory: LangChain + FalkorDB](https://www.falkordb.com/blog/building-ai-agents-with-memory-langchain/): Learn to build AI agents with memory using LangChain and FalkorDB. This integration enables context-aware AI applications, leveraging graph databases for enhanced capabilities.
- [FalkorDB V4.8: Competing vendors require
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