FalkorDB

QueryWeaver just crossed 1,000 🌟 on GitHub! 🎉 If you love the idea of turning plain English into accurate SQL using graph-powered schema understanding, drop us a star to help keep the momentum going! 🚀 👉 github.com/FalkorDB/Query…

Tired of your AI agents having the memory of a goldfish? 🐠 Stop re-explaining your projects every time you open a new chat! Discover how to cure "AI Amnesia" by giving your agents a real, long-term memory. By using Knowledge Graphs, your AI can map out entities and relationships naturally as you chat, keeping context sharp, accurate, and token costs low. Learn how to build it using @FalkorDB, @cognee_ , and @openclaw : falkordb.com/blog/curing-ai…

Check out how @FalkorDB uses sparse-matrix operations to deliver sub-millisecond multi-hop traversals for accurate GraphRAG: Beyond Vector Search 💻🔥 A post by @g_korland falkordb.com/blog/code-grap…

Vector search retrieves code that looks similar, not code that is actually connected. Stop flattening your codebase into text chunks and missing call chains. The secret to chatting with complex repositories is a code graph that maps actual dependencies, functions, and imports.

When I published @falkordb on @orynth yesterday afternoon, I didn't really image how crazy it's going to look. It has been like this for 17 hours straight! I can't stop looking on this graph skyrocketing!

Are your AI agents suffering from digital amnesia? 🧠 It's time to give them a real brain! Join us next week as Gal Shubeli presents @FalkorDB's groundbreaking GraphRAG-SDK results in our webinar: "Mastering Knowledge Graphs and Agentic Memory." luma.com/41jl9k7r?tk=9U…

Heading to SF for the @aiDotEngineer World's Fair? Let’s catch up in person! Look for the bright orange shirts 🍊at the @falkordb booth to see how we handle production AI scaling with sub-millisecond graph traversals. Come check out our live demos: GraphRAG & Agentic Memory, QueryWeaver & Code-Graph See you there!

Today we decided to do a fair launch on @Orynth to bring more awareness to what we're building and let the community take part in the journey from day one. @FalkorDB is a blazing fast graph database designed for AI applications. It is built for real time relationship queries at scale, with support for multiple graphs in a single deployment for efficient multi tenant applications. Instead of relying only on vector search, FalkorDB traverses explicit relationships so AI systems can reason across connected data more accurately. That makes it useful for multi hop reasoning, code navigation, fraud detection, and knowledge graphs. Launching a market on Orynth helps bring more eyes to FalkorDB and gives the community a simple way to discover what we are building while the team keeps shipping graph native AI infrastructure. The official contract address: C1mg2ddme7Hpwjmxngr1AfrwRSmLqL1CVHPzUmapEory Please make sure you only use the CA shared from our official channels. More updates coming soon.

Speed is everything. @falkordb's patch cycles are proving that in the agentic era, code optimization happens in near real-time. Check out the lightning-fast fixes rolling into v4.18.10, built for the next generation of AI-driven data. 📉⚡️ github.com/FalkorDB/Falko…

Mom, I made it! 🗽 Surreal seeing @FalkorDB up on the @NasdaqExchange tower in Times Square! Huge thanks to the amazing @Deloitte Launchpad team for all the support in helping us reach this milestone. Next stop: ringing that opening bell for the IPO! 🔔

We are going to Give Your Agents a Brain: Mastering Knowledge Graphs and Agentic Memory. Join us! luma.com/41jl9k7r?tk=1d… via @LumaHQ

What an amazing Day 1 at Snowflake Summit! ❄️ We are officially fueled up, energized, and ready to roll for Day 2. Stop by our booth #2719 today to chat with the team and see how we're bringing the ultimate Graph Database to Snowflake! #SnowflakeSummit

FalkorDB is now available as a Document Store in Haystack. Use FalkorDBDocumentStore to store documents and vectors in a graph format, pair it with FalkorDBEmbeddingRetriever to retrieve documents by semantic similarity, and use FalkorDBCypherRetriever for graph-based queries. This makes it easy to build retrieval pipelines that leverage both vector search and graph relationships. @falkordb is built as an extension of Redis, making it lightweight and efficient for applications that need real-time graph and vector capabilities. 🐍 pip install falkordb-haystack 🔗 haystack.deepset.ai/integrations/f…

FalkorDB is proud to be a Lodge Partner at Snowflake Summit '26 (June 1–4). 🏔️ Stop by our booth #2719 in the Lodge area to chat about ultra-fast graph databases, Knowledge Graphs, and how we're powering the future of GenAI. Let’s connect drop a comment if you'll be there! 🤝

@Mariandipietra @Cloudflare 😍

Hey @Cloudflare, what do you think about adding @falkordb to your product offering?

GraphRAG-SDK v1.1.0: Better retrieval on complex docs, faster updates on changing data. Anyone ingesting Markdown documentation, technical specs, or data-heavy reports where a table/list split across two chunks would corrupt retrieval results. benefits! github.com/FalkorDB/Graph…

🛑 20 May, we're walking through a live demo about discovering connections SQL can't w/ Graph Analytics using FalkorDB deployed as a native app on @Snowflake . No: separate pipeline, data migration or new infrastructure. luma.com/7zkmeqcx

SQL hits a wall when your data is deeply interconnected. FalkorDB brings native graph computation directly into your Snowflake environment. [Save the date] 21 MAY: See the Connections Your SQL Can't: Graph Analytics with FalkorDB & Snowflake. luma.com/7zkmeqcx

Token costs spiking. Responses too slow. Users don't trust the answers. All three are retrieval problems. GraphRAG SDK 1.0 is out. Ranked #1 on GraphRAG-Bench against 8 systems. Fewer LLM calls, grounded answers, predictable cost. Open-source: github.com/FalkorDB/Graph…

We signed two enterprises this month. Here are some Agentic infra essentials: Data Pipeline: CocoIndex @cocoindex_io Real-time: Iggy @laserdatainc Graphdb: @falkordb Pretty much