Author: Robert Silén
-
Laravel 13 now supports MariaDB Vector natively
If your Laravel application runs on MariaDB, you can add semantic search to it without a second database, an external vector service or an extra package. Since Laravel 13.28, vector columns, vector indexes and similarity queries work on MariaDB out of the box. A large part of that work came from community contributors, including Mohamed Touhami Rhaima.
Until this summer, Laravel’s built-in vector search was a PostgreSQL feature: it assumed pgvector. Laravel’s AI SDK documentation now reads: “Vector queries are currently supported on […]
-
MariaDB adoption is growing, and the way people get it is changing – Adoption Index 2026-09
The MariaDB Adoption Index is up 126% in a year. More people are downloading MariaDB, more people are contributing to it, and more projects are building on it than at any point since we started measuring.
At the same time, the numbers show something else: the way people acquire and discover MariaDB is changing. Some of our older metrics are falling – not because MariaDB is, but because the channels they measure are.
The index combines 24 metrics – downloads, […]
-
Launching MariaDB’s Database Survey 2026
We want to know how you’re really using MariaDB — and databases in general. Not the marketing version or the one-off case study. The real story: what you’re building, how you are using it, what’s working, and what’s frustrating.
Last year we ran the first State of MariaDB survey. 275 of you took part, and the results became a public report linked from mariadb.org/survey. Now we’re back with the 2026 edition — the second annual survey — fresh questions, tailored […]
-
MariaDB Vector in Laravel: insights on choosing an embedding model
Update, October 2026: Since Laravel 13.28 (August 2026), vector columns, vector indexes, the AsVector cast and vector similarity queries on MariaDB are built into Laravel itself, with no package needed. See Laravel 13 now supports MariaDB Vector natively. Erik’s package remains an option for Laravel 12, and his findings on choosing an embedding model apply whichever you use.
laravel-mariadb-vector is an open-source project by Erik Ros, bringing MariaDB’s native vector search to Laravel’s Eloquent ORM. In his guest post, Erik shares how it works, and […]
-
Drupal recommends MariaDB
MariaDB is now clearly listed as the recommended database in Drupal’s official documentation. Following community discussion on Drupal.org, the Database server requirements now lists MariaDB first, and identifies it as the recommended database for Drupal 10, 11, and 12. Drupal is a major open source content management system—a flexible platform used by a substantial share of websites globally.
We’re glad to see this. Recognition matters because MariaDB is often used but documented as MySQL, going unnoticed under the hood—and when […]
-
State of MariaDB 2025: The Results Are In
In October 2025, we launched the first State of MariaDB Survey to learn how the community really uses MariaDB. Today, we’re excited to share the results.
Read the full report →
Why we did this
We wanted to move beyond assumptions and get real data from the people who work with MariaDB every day—developers, DBAs, architects, consultants, and everyone in between. The goal was simple: understand how MariaDB is actually being used so we can make it better.
What we […]
-
Multimodal-Metadata-Hub for MariaDB Vector – Innovation 2nd place at MariaDB BangPypers Hackathon 2025
We recently announced the winners of the MariaDB Python Hackathon. We sat down with the Innovation track second place winners to learn more about the team and their submission.
Sunny Kumar, Abhijeet Dhanotiya, Anuj Gupta, Tushan Kumar Sinha, and Anand Vyas developed Metadata-Hub, a multimodal semantic search application using MariaDB Vector and OpenAI’s CLIP model. They were interviewed by Robert Silén, Community Advocate and Kaj Arnö, Executive Chairman of MariaDB Foundation. For the recorded interview, watch it on Youtube, or read the interview below.
Before we […]
-
Adaptive Query Optimizer for MariaDB Vector – Innovation Winner of MariaDB Python Hackathon 2025
We recently announced the winners of the MariaDB Python Hackathon. We sat down with the Innovation track first place winners to learn more about the team and their submission.
Aakanksha Singh and Mihir Phalke developed an Adaptive Query Optimizer for MariaDB Vector, addressing performance challenges in vector similarity search operations. They were interviewed by Robert Silén, Community Advocate and Kaj Arnö, Executive Chairman of MariaDB Foundation. For the recorded interview, watch it on Youtube, or read the interview below.
Introducing […]