HelixDB

Query HelixDB directly in Python 🐍 You can now download our Python SDK and use the HelixDB DSL to query your data directly inside your Python projects. No extra query language. Just Python. Docs here: https://lnkd.in/gKwpDREz

HelixDB just crossed 5,000+ GitHub Stars! 🌟 📈 We want to give a special thanks to the amazing HelixDB community that has helped us get this far. To our angels, investors, and Y Combinator: thank you for believing in us and enabling us to work on this full time. And of course, to the HelixDB team: thank you for turning this project from an idea into a reality. We’re just getting started! 🚀

LAUNCHING: Helix-DB GO DSL go 💃 🕺 Just like our Rust and TypeScript DSLs, you can now query HelixDB with GO directly in your production code.

Get busy this weekend with HELIX CHEF! 👩🍳 Go from ZERO to PRODUCTION with a single CLI command! 1. Install the CLI 2. Run `helix chef` 3. Describe your project Watch your coding agent build an entire local Helix project!

🚨 WE JUST KILLED GRAPH QUERY LANGUAGES 🚨 HelixDB can now be queries directly in TypeScript. 🤯 No Cypher. No Gremlin. No HQL. Just native TypeScript. Modern apps are already written in TypeScript. Your database should feel native to it too. We’re building the next generation of graph + vector infrastructure for AI applications at HelixDB 🚀 Check out the TypeScript DSL: https://lnkd.in/eD7G6xie

Today we’re introducing Helix-DB v2 🚀 Over the last few months we’ve been rebuilding major parts of the database to make Helix significantly more flexible, easier to deploy, and better suited for modern AI workloads. Some of the biggest changes: 🔎 New query methods You can now query HelixDB dynamically using JSON queries, without recompiling the database every time you want to ship new logic. For teams that want maximum performance and type safety, we also added a Rust DSL for compiled queries 🦀 Typescript DSL + GQL integrations are also in progress. ⚡ Multiple runtime modes Helix can now run: • Fully in-memory for maximum performance • On-disk for local development and MVPs • Backed by object storage for affordable production deployments 🪣 📈 Query insights We built tooling into the dashboard to help developers understand query performance and optimize bottlenecks. 🌐 Vectors on both nodes and edges You can now store multiple vectors across nodes AND relationships. This opens up a lot of interesting possibilities for: • AI memory systems • GraphRAG • Semantic traversal • Relationship-aware retrieval systems A huge amount of engineering has gone into this release from our small team over the last few months 🔥 Still a lot more coming soon.

🚀 We’re launching Helix Enterprise. A horizontally distributed graph database that scales better and cheaper than anything else on the market. ⚡ For years, graph databases have had the same problem: Great idea. Bad economics. 📉 They get expensive fast, struggle to scale cleanly, and become operationally painful in production. 😵💫 So we built something different. 🛠️ Helix Enterprise is designed for graph workloads that actually need to run at scale — across distributed infrastructure, with strong performance, and without absurd cost. 🌐 This is for teams building: 🔗 knowledge graphs 🎯 recommendation systems 🛡️ fraud systems 🧩 entity resolution 🤖 AI retrieval and memory layers 🏗️ large-scale relationship-heavy applications If your graph database falls over when the workload gets real, this is for you. 💥

This morning we hit 4,000 GitHub stars!!! 🤯⭐️ That makes us the FASTEST growing graph database company ever. 📈 The crazy part is we started this by solving our own problem. And yet after a year of finding our customers and iterating with them, we're now building something people really want. Super excited with what we will be bringing you in the coming months.

We just launched HelixDB (YC X25) Cloud ⛅️🎉 HelixDB is a graph-vector database built from scratch in Rust. Native graph storage. Native vector indexing. Why this matters: Hybrid retrieval (graph + semantic) shouldn’t require multiple systems. In HelixDB, traversals and vector search run in the same engine. That means: • Lower latency • No data duplication • Stronger consistency • Simpler architecture HelixDB Cloud now lets you spin this up instantly. If you’re building: – GraphRAG – Agent memory systems – Fraud detection – Identity & access graphs - Or any other graph applications... This is for you. Try it: https://helix-db.com/login Would love feedback from the community :)

Reminder to all those interested! See those coming tomorrrow :)