
FalkorDB Now Fully Supported in G.V() 3.38.90
G.V() 3.38.90 brings full FalkorDB support, letting AI developers connect their LLM-optimized graph database for instant visualization. Perfect for agentic AI applications and advanced chatbots.

G.V() 3.38.90 brings full FalkorDB support, letting AI developers connect their LLM-optimized graph database for instant visualization. Perfect for agentic AI applications and advanced chatbots.

Zep founder Daniel Chalef joins FalkorDB, details Graphiti, a graph framework for real-time LLM memory and RAG. It handles dynamic data better than vector search.

This maintenance and enhancement release delivers significant performance improvements for parameter-heavy operations and strengthens operational reliability across cloud deployments.

FalkorDB achieves SOC 2 Type II certification, demonstrating enterprise-grade security controls for multi-tenant graph database operations and mission-critical applications.

Knowledge graphs represent complex relationships as nodes and edges. This workshop demonstrated practical implementations through two systems: VCPedia for venture capital data extraction and Fractal KG for self-organizing graph structures.

Bank of America proves small LLMs and GraphRAG deliver scalable, compliant AI with low latency and precise context retrieval in production environments.

Developers voted FalkorDB HackerNoon Startup of the Year 2024 for Tel Aviv after shipping sparse-matrix storage, AVX-accelerated queries, and multi-tenant clustering with sub-10 ms tail latency.

Without AI-ready data, most generative AI projects fail. Learn to standardize enterprise data with graph databases like FalkorDB for scalable AI success.

Learn about integrating Graph Neural Networks (GNNs) with LLMs for precise relational modeling and improved AI performance in fraud detection, healthcare, and more.
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.