AI
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
VillageSQL
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
Extension
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
Extension
An engineer leaves your company. You disable their single sign-on account, and their access to the wiki, the cloud console, and the CI system goes with it. Typically, access to database resources doesn't follow such a simple plan. Database user and role maintenance too often happens within
MySQL
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
Extension
When something goes wrong inside MySQL, the server says so in the error log. It's what administrators already watch. Every entry carries a severity and an error code, and you can query it from performance_schema.error_log like any other table. It is the server's
VillageSQL
MySQL's string matching is precise by design. LIKE '%shirt%' finds "shirt." It won't find "shrt" or "shrit" or anything a user actually typed when they meant "shirt." Handling that in MySQL means regex patterns that grow
VillageSQL
You have a table. You need to serve it over HTTP. The standard path requires you to write a service in Node or Python or Go, wire up routes, translate query parameters into WHERE clauses, serialize rows as JSON, add auth middleware, deploy it separately from the database, and then
MySQL
VillageSQL launched with C++ as the language for writing extensions — C++ is familiar territory for MySQL developers. Rust has become a go-to language for systems and infrastructure developers: the same people who build database connectors, storage engines, and performance-critical services. VillageSQL's new Rust SDK adds it
VillageSQL
VillageSQL is a tracking fork of MySQL that adds the VillageSQL Extension Framework (VEF). Extensions are written in C++ (with a Rust SDK coming soon), packaged as .veb bundles, and installed with SQL. The fastest way to understand what VEF can do is to build something with it. To make
VillageSQL
VillageSQL Server 0.0.4 is now available (and marked as the stable release for installs). 0.0.4 takes the parameterized types and SQL integration from 0.0.3 and extends them in two directions: * smarter server reasoning (inference rules, custom aggregates) * operational completeness (config, metrics, secrets management) Extensions
MySQL
Most AI integrations with a database follow the same pattern: your application fetches rows, ships them to an AI API, waits for a response, then writes the result back. It works, but it means adding a service layer to do something that's conceptually simple—apply a function to