The latest from the MySQL community

So I figured it was about time I documented how to build persistent memory for AI agents using the databases you already know. Not vector databases - MySQL and Neo4j.

This isn't theoretical. I use this architecture daily, handling AI agent memory across multiple projects. Here's the schema and query patterns that actually work.

The Architecture

AI agents need two types of memory:

• Structured memory - What happened, when, why (MySQL)
• Pattern memory - What connects to what (Neo4j)

Vector databases are for similarity search. They're not for tracking workflow state or decision history. For that, you need ACID transactions and proper relationships.

The MySQL Schema

Here's the actual schema for AI agent persistent memory:

-- Architecture decisions the AI made
CREATE TABLE architecture_decisions (
    id INT …

This post covers a hands-on walkthrough of MySQL 8.0's JSON functions. JSON support has been in MySQL since 5.7, but 8.0 added a meaningful set of improvements — better indexing strategies, new functions, and multi-valued indexes — that make working with JSON data considerably more practical. The following documents several of the most commonly needed patterns, including EXPLAIN output and performance observations worth knowing about.

This isn't a "JSON vs. relational" debate post. If you're storing JSON in MySQL, you probably already have your reasons. The goal here is to make sure you're using the available tooling effectively.

Environment

mysql> SELECT @@version, @@version_comment\G
*************************** 1. row ***************************
        @@version: 8.0.36
@@version_comment: MySQL Community Server - GPL

Testing was done on a VM with 8GB RAM and …

Modern applications often rely on multiple services to provide fast, reliable, and scalable responses. A common and highly effective architecture involves an application, a persistent database (like MySQL), and a high-speed cache service (like Valkey).

In this guide, we’ll explore how to integrate these components effectively using Python to dramatically improve your application’s performance.

Understanding the 3-Server Architecture

In our example, the setup looks like this:

Application(172.31.68.72)
   |
   |-- MySQL client  -->  Percona Server (172.31.67.228)
   |
   |-- Valkey client -->  Valkey Server (172.31.22.118)

The Application: The brain of the system. It decides when to query the database and when to rely on cached data.

Valkey: An in-memory key-value store optimized for extremely fast reads and writes.

MySQL: The …

What Happened at the Summits

We just wrapped up two MySQL Community Summits – one in San Francisco in January, and one in Brussels right before FOSDEM. The energy in the rooms: a lot of people who care deeply about MySQL got together, exchanged ideas, and left with a clear sense that we need to act.

The goal was to gather the people who care about MySQL, have an open exchange of ideas, and leave with action points.  We had end users, contributors, and vendors all in the same room, all agreeing on one thing: MySQL matters, and we all want MySQL to grow in popularity, not to follow a trajectory of decline.

Where MySQL Stands Today

MySQL is declining in popularity. PostgreSQL has become the default choice for new projects. MySQL is at genuine risk of becoming irrelevant if we don’t do something about it. …

Right before FOSDEM kicked off, the preFOSDEM MySQL Belgian Days returned to the usual place in Brussels for two packed days (Jan 29-30, 2026). The format stayed true to what makes this event special: a friendly, hallway-track-heavy gathering with serious technical content — this year running two parallel tracks and the grand final: the RockStars […]

We are pleased to introduce the ability to export MySQL HeatWave backup data directly to an OCI Object Storage bucket in your tenancy, enabling a one-step process to create an exported backup via the Console or API. This process creates a logical dump from the backup without utilizing DB system resources, thereby minimizing the impact on the […]

As we mark the milestone of MySQL’s 30-year anniversary, the celebrations around the globe have been a testament to the widespread impact and popularity of the Dolphin. This week’s annual preFOSDEM MySQL Belgian Days in Brussels are not only an opportunity to celebrate, but also a chance for Oracle to share some key updates on […]

As AI workloads become standard in modern applications, engineering teams face a familiar dilemma: MySQL is already the system of record, but vector search typically requires bolting on a separate database. MyVector and ProxySQL solve this without fragmenting your data stack.

The new protocol dissector for X Protocol in MySQL was just merged to the master branch in Wireshark. To get it build Wireshark from the master branch or wait for the next release.

This protocol is using Google Protobuf, which makes it much easier to work with than the regular MySQL protocol.

See also: https://dev.mysql.com/doc/dev/mysql-server/latest/page_mysqlx_protocol.html 

If you like what Wireshark does, consider donating on https://wiresharkfoundation.org/donate/ 

ProxySQL v4.0 adds a transparent AI layer at the proxy — RAG pipelines, NL2SQL, and an MCP server for AI agents — without touching your database or application code.