The latest from the MySQL community

On paper it’s a boring release. No new tools, no new flags, nothing to reconfigure. In practice it’s one I’m glad I didn’t skip: it closes 37 known vulnerabilities that the server could actually reach, and I found them more or less by accident.

It started as a compatibility check

I had MySQL 8.4, 9.7 and 26.7 running on my test box, plus MariaDB 12.3. So I pointed the MCP server’s test suite at all of them. Mostly to tick a box before moving on to something more fun.

The code was fine. Every version passed.

MySQL 26.7 and MariaDB 12.3 join the matrix

Every pull request now runs the full integration suite against six servers:

• MySQL 8.0, 8.4, 9.7 and 26.7
• MariaDB 11.4 and 12.3

26.7 is the first Innovation release under Oracle’s new calendar versioning. If you follow MyVector, you know I’ve …

PostgreSQL has a rapidly evolving vector ecosystem. MySQL is earlier on that road, but the community is hard at work catching up. MariaDB ships its own HNSW index, Google engineers have shared a ScaNN-based vector index on MySQL's own vector index proposal, Percona is building an HNSW index inside InnoDB, and VillageSQL is building vector search as an extension with vsql-vector.

We want vector search on MySQL to be something that teams can …

Type “a heist that goes wrong in a snowy town” and get back real films, with posters, in a few milliseconds. The vector search behind it runs inside MySQL, with no separate vector database.

Movie Finder is the new demo app that ships with MyVector. It searches up to 1,035,695 TMDB movies by meaning, not keywords. One docker compose up gives you the whole thing: MySQL 9.7 with the MyVector component, a loader, and a small web app.

Try it live: https://demo.myvector.online/

We built it to answer the questions people ask us most. Does vector search in MySQL hold up at a million rows? Can I mix it with ordinary WHERE filters? What happens when I insert a new row? The demo shows the answers on the page, with the SQL that ran under every result.

Live: What you can do on the page

Every feature on the …

AI database governance can get overlooked when teams rush to connect AI tools to production data. IBM’s 2025 research found that 97% of organizations that reported a breach involving an AI model or application lacked proper AI access controls. The risk is easy to see. Give an AI agent too much access and it can […]

The post Database governance in the AI era: Framework, risks and best practices appeared first on Devart Blog.

The Model Context Protocol (MCP) has become a standard way for AI agents to discover the tools an application, database, or service offers. Claude Code, Codex, Cursor, Antigravity, et al. can connect to an MCP server, ask it what tools are available, and call these tools instead of figuring out what they can or can't do on the fly or piecing together API calls. Setting up an MCP server for a database usually means running a separate process that holds a database credential and turns tool calls into queries. Then you have another process to deploy, another place a credential lives, and a set of guardrails that sit outside the database.

The vsql-mcp extension from VillageSQL takes a different approach. It puts the MCP server inside the database. Install it, set a handful of global variables, and your MySQL server itself serves MCP over Streamable HTTP from a background …

TL;DR

Percona Server for MySQL 9.7.2-2 now supports DISTANCE() for vector similarity scoring directly in SQL (COSINE, EUCLIDEAN, MANHATTAN, DOT metrics). This is the compute primitive you need to rank or filter embeddings by similarity directly in SQL. ANN indexing (e.g. HNSW, IVF) is the next milestone for fast large-scale similarity search; and this function provides the scoring layer that indexing strategies will further accelerate.

Why we’re adding this

MySQL’s native DISTANCE() and VECTOR_DISTANCE() functions are only available in HeatWave MySQL on OCI, not included in Community or Commercial MySQL, and limited to three metrics (COSINE, DOT, EUCLIDEAN). Percona is bringing the same capability to anyone running Percona Server for MySQL on any supported platform.

MySQL 9.7 already supports the VECTOR data type (TO_VECTOR() and FROM_VECTOR() functions) for storing embeddings. DISTANCE() …

Percona gives us room to work on our own AI-assisted projects, and I used mine to fix a problem I kept running into. Every time I wanted to try a new database feature, debug something tricky, or reproduce a customer issue, I ended up rebuilding much of the same infrastructure: DNS, TLS, Docker networking, database topologies, users and test data. Over the years, I wrote scripts to automate this but I still found myself copying and pasting post-installation steps from one lab to the next.

That repetition is what turned into DBCanvas, a self-hosted lab for designing, deploying, operating, and stress-testing multi-node database stacks on my own machine. Just design a topology on a canvas, click Deploy, and get real running nodes connected to the services and supporting infrastructure your test requires. Then, use the tools built into it or third party tools to load those …

There are a few cryptography tasks that are common to many backends. For example, you should store passwords such that a database leak doesn't expose them, you should sign payloads so the receiving side can verify them, you should keep a column's data unreadable outside the database, and you should mint tokens an attacker cannot guess. MySQL's built-in functions cover part of that ground but fall short for many users. The SHA2() function will hash a password, but nothing salts it for you, so two people who pick the same password end up with the same stored value. MySQL does not have a built-in HMAC function. An HMAC is the keyed hash a receiver uses to tell a real message from a forged one.

When a database doesn't solve a problem natively, the work invariably moves up into application code, where every service reimplements it just a little bit differently. This adds ongoing maintenance complexity.

The …

AI agents can already write SQL, inspect schemas, and work through multi-step database tasks. But what happens when they start acting inside the database itself. Read the full article to see where that shift leads, what still needs human control, and how database IDEs fit into the picture.

The post Will AI agents replace database IDEs? The future of database development  appeared first on Devart Blog.

VillageSQL Server 0.0.6 is now available. This release advances the mainline to MySQL Server 8.4.11 and adds support for MySQL Server 9.7.2 and Percona Server 8.4.10.

Highlights of this release include the following:

• An extension can now log you in, so your identity provider decides who gets into the database.
• Extensions can call the server's own internal component services, which opens up a large part of the MySQL surface area.
• A privilege of its own now covers extension management, so you can grant that and nothing else.
• If you build a custom type incorrectly, you find out when you compile the extension or when you install it, rather than when someone runs a query.

VillageSQL now runs on MySQL Server 9.7 and Percona Server 8.4

VillageSQL Server 0.0.6 adds a mysql-9.7 build that tracks the MySQL Server 9.7.2 tree, and a percona-8.4 build …