We're live on Product Hunt with Spectron, the memory and knowledge layer for AI agents built on SurrealDB. Come share your thoughts and drop your questions in the thread; we'll be there all day. 👉 sdb.li/4fnDYEK

1/ A few years ago we made a bet that the database should be multi-model in one engine, in one transaction. Most people thought that was a niche idea. Agent memory is where that bet pays off.

Agents are getting good at acting. They're still bad at remembering. Spectron, the memory and knowledge layer for AI agents built on SurrealDB, addresses this. Early access opens today. Learn more. 👉 sdb.li/4fXn8g4

Agent memory you can trust. 3 June 2026

We have been working on something. Building AI agents? Tomorrow is for you. 3 June 2026.

1/ Databases are entering a weird new era. Not because of AI hype. Because for the first time in decades, databases are being asked to behave less like storage engines… and more like memory systems. Today we shipped SurrealDB 3.1. And buried inside the release is something important: DiskANN.

SurrealDB 3.1 is here and builds on the foundations of 3.0, with a focus on stability, a second approximate-nearest-neighbour vector index in DiskANN, GraphQL upgrades, and significant security hardening. Explore the highlights.👉 sdb.li/3Q7X4Ey

#NVIDIAGTC is live, and we're at booth #4026! Come meet founders @tobiemh & @jaimemh, and chat with Matthew Penaroza & Ignacio Paz to learn why SurrealDB is becoming the go-to database for AI agents, handling core state, contextual memory, and connected data in one place. 👋

We rebuilt SurrealDB’s core engine in our latest major release, unlocking significant performance gains over prior versions. Benchmarks show graph queries 8–22× faster, with more improvements already on the roadmap. Dive into the details. 👉 sdb.li/4kOBVuc

SurrealDB 3.0 launches with $23M in new funding and a pitch to replace multi-database RAG stacks with a single engine that handles vectors, graphs, and agent memory transactionally. venturebeat.com/ai/surrealdb…

Today we are releasing @SurrealDB 3.0. With this version, we have strengthened the core architecture to better support modern, AI-driven applications. Rather than treating graph, document, relational, and vector capabilities as separate concerns, 3.0 brings them together within a single engine and unified query layer. The goal is straightforward: reduce fragmentation and provide developers with a consistent foundation to build on. AI systems place different demands on infrastructure. They require structured data, semantic search, and rich relationship traversal to operate reliably at scale. SurrealDB 3.0 supports these patterns natively, allowing context and data to exist within one coherent system rather than being distributed across multiple services. Significant work has gone into improving stability, performance, and production readiness. We have refined how data is stored and processed, strengthened transactional guarantees, and simplified the overall developer experience. The result is a database that is more predictable under load and easier to integrate into real-world deployments. This release would not exist without the dedication of the team and the thoughtful feedback from our community. We are grateful for the role both have played in shaping 3.0. If you are building intelligent, data-intensive systems, SurrealDB 3.0 is ready to explore. You can watch the launch and start building today. surrealdb.com/3.0

SurrealDB 3.0 is coming, mark your calendar! On February 17, 2 PM GMT we’ll unveil our latest major release, sharing what’s changed under the hood and how it reshapes the way you model and query data, especially for modern, AI-driven applications. 👉 youtu.be/USg8ZQC5mQc

A schema defines your database’s structure and rules. Early definition ensures consistent data storage, linking, and behaviour throughout your project. Some tips from our own @mithridates show you how to design one that works for you. 👉 sdb.li/4ly1PkX

Our Rust SDK is the primary method for interacting with our multi-model database from client–side, server-side apps, systems, APIs, embedded systems, and IoT devices. Check out 7 tips and tricks for optimising your use of the SDK.👇 sdb.li/4ljfYmI

Eager to learn how our multi-model database stacks up against other databases, whether it be SQL, NoSQL, and others? Join us on this benchmarking journey. 👉 sdb.li/4hs28vY

We’re starting 2025 with a new release of our multi-model database you’ve all been waiting for. Why? Besides improved performance, stability, and better relationships for graph and record links, our benchmarking results are available! 👉 sdb.li/4hOzYem

Our next AMA with @tobiemh is on February 27. If you’re curious about the latest updates to our multi-model database, join us at 16:00 GMT on Discord. 👉 sdb.li/4jTtUmy

We've now released our 1.0 stable version of our Python SDK. Learn more. 👉 sdb.li/4hfTzEy

Getting started with our multi-model database? With the SurrealDB Fundamentals course, get access to practical hands-on learning and master the five core parts of building a production-ready database. Start building your skills. 👉 sdb.li/4hcQHZa

Learn about the different forms of authentication built into our multi-model database to support your use cases. @Obinnaspeaks outlines how to secure your apps with users in the correct groups. Watch the full tutorial. 👉 youtu.be/cGAxH9FezUY