FalkorDB
The blazing-fast Graph Database for LLM RAG
FalkorDB launched on December 7, 2023 with 4 votes, #1,562 of 3,780 launches that month. The site was still online in September 2026, 2 years on.
What it does
FalkorDB is a graph database that uses GraphBLAS under the hood and OpenCypher to enable efficient RAG of complex data sets.
FalkorDB is a graph database optimized for GraphRAG, delivering accurate, relevant AI/ML results with reduced hallucinations and enhanced performance.
Combine LLMs with domain-specific knowledge graphs to reduce hallucinations and enrich AI responses. Enable natural language queries, traceable retrieval logic, and hidden insight discovery for smarter decision-making and faster AI deployment. Combine graph traversal with vector search to create personalized agentic AI applications. Connect user profiles, preferences, and activities to deliver accurate, explainable recommendations with near real-time adaptability to changing contexts. Build context-aware chatbots by integrating knowledge graphs for entity extraction, fact linking, and relationship mapping. Enable real-time recommendations by correlating user behavior, product data, and…from falkordb.com
Does a similar job
all alternatives →- FOFalkorDB – Open-source graph database major update (C/Rust)2025 · ▲7
Hey HN, I’m Roi, one of the co-creators of FalkorDB. We’re a growing team working on a graph database designed for production workloads and GraphRAG systems. The new release (v4.10.0) is out, and I wanted to share some of the updates and ask for feedback from folks who care about performance, memory efficiency in graph-heavy systems. FalkorDB is an open-source property graph database that supports OpenCypher (with our own extensions) and is used under the hood for retrieval-augmented generation setups where accuracy matters. The big problem we’re working on is scaling graph databases without…
FalkorDB fork from RedisGraph bringing it back to life2023 · github.com · ▲11The team behind RedisGraph decided to take a stab at bringing this disruptive technology back to market. We plan to rebrand it and release it as a stand alone product, following the same guidelines we have followed for the last 6 years: * Working in the open with the community * Always provide superior performance. * Easy to adapt
FastGraphRAG – Better RAG using good old PageRank2024 · github.com · ▲457Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
LatticeDB – Like SQLite but for graph databasesAug 2026 · github.com · ▲190We have been using graph DBs more and more at work. I found them painful to work with locally and decided to try and build something better.
- IBIn-Browser Graph RAG with Kuzu-WASM and WebLLM2025 · blog.kuzudb.com · ▲158
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
HelixDB – Open-source vector-graph database for AI applications (Rust)2025 · github.com · ▲237Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…
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