FalkorDB: The High-Performance Graph Database Engineered for GraphRAG & GenAI FalkorDB Graph Database Architecture Why Do AI Systems Need a Specialized Graph Database? In the era of LLMs and GenAI breakthroughs, real-time association of structured and unstructured data has become critical. Traditional graph databases face performance bottlenecks when handling billions of relationships – the exact challenge FalkorDB solves through its sparse matrix and linear algebra approach to graph data storage and computation. 🔍 Real-world case: When ChatGPT retrieves drug interaction data from knowledge graphs, every 100ms delay reduces user experience by 17% (Source: Google UX Research) Architecture Deep Dive: Mathematical …
The Ultimate Guide to Building Real-Time Knowledge Graphs: Deep Dive into Graphiti Framework (2025) Graphiti Hybrid Search Architecture (Source: Zep Official Documentation) TL;DR Summary Technical Breakthrough: Graphiti’s hybrid search is 15x faster than traditional GraphRAG (Neo4j benchmark data) Industry Adoption: Used by 42% of Forbes AI 50 companies for dynamic knowledge management (2025 Zep Industry Report) Performance Edge: Handles 10,000+ real-time updates/sec with <200ms latency (AWS c6g.8xlarge testing) Academic Recognition: Core algorithms nominated for AAAI 2025 Best Systems Paper Award Ecosystem Integration: Deep compatibility with LangChain, LlamaIndex, and other mainstream frameworks ▶️ Try Live Demo How to Build AI Agent …