Category Archives: Using MariaDB
The day has come that you have been waiting for since the ChatGPT hype began: You can now build creative AI apps using your own data in MariaDB Server! By creating embeddings of your own data and storing them in your own MariaDB Server, you can develop RAG solutions where LLMs can efficiently execute prompts based on your own specific data as context.
Why RAG?
Retrieval-Augmented Generation (RAG) creates more accurate, fact-based GenAI answers based on data of your own choice, such as your own manuals, articles or other text corpses. RAG answers are more accurate and fact-based than general Large Language Models (LLM) without having to train or fine-tune a model.
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Continue reading “Try RAG with MariaDB Vector on your own MariaDB data!”
We have been in festive mode this week, celebrating fifteen years of MariaDB. You may have seen our very own Ian Gilfillan’s blog MariaDB Server turns fifteen!, or the blog of Alejandro Duarte of MariaDB plc, MariaDB Server Turns 15! Here Are 15 Reasons Why Developers and DBAs Love It.
Technical overview by the creator of MariaDB Server
Now, MariaDB Server’s creator Michael »Monty« Widenius has chimed in, with a lot of technical detail. Hardly anybody is better equipped to create this technical overview, Celebrating 15 years of MariaDB.
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We’re here, we’re open source, and we have RDBMS based Vector Search for you! With the release of MariaDB 11.6 Vector Preview, the MariaDB Server ecosystem can finally check out how the long-awaited Vector Search functionality of MariaDB Server works. The effort is a result of collaborative work by employees of MariaDB plc, MariaDB Foundation and contributors, particularly from Amazon AWS.
Previously on “MariaDB Vector”
If you’re new to Vector, this is what’s happened so far:
- We blogged a number of times about our view of where Gen AI belongs in MariaDB Server
- We showed a first demo in February at our FOSDEM Fringe Event
- We launched a project page on mariadb.org/projects/mariadb-vector/, containing a number of videos
- We went on stage at Intel Vision in London, with AI everywhere
- We blogged about Amazon’s take on Vectors and MariaDB, in “MariaDB is soon a vector database, too“
The main point: MariaDB Vector is ready for experimentation
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Users of open source software don’t always share their stories, simply because they are satisfied. That’s why we were delighted to accept an offer from database expert Richard Bensley to share why he has repeatedly used MariaDB over the years.
I had a chat with Richard and learnt that he has seen MariaDB as a user, customer, and even an employee of MariaDB. Despite experimenting with other solutions, new and old, his passion for MariaDB and the people behind hasn’t faltered.
Richard has been using MariaDB in large scale production since 2012 for financial platforms, CRMs and e-commerce for regional and international use.
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Both MariaDB and MySQL have been around a long time now, and there is always a difficult balance between maintaining compatibility whilst also solving security issues that arise. With the latest bugfix releases of MariaDB, we had to break compatibility a little to improve security, but there are workarounds. We figured we should explain the reasons behind it and how to make things as painless as possible for you.
The Problem
The problem we were solving, and for various reasons we had to do it very quickly, is that it is possible to generate a malicious MariaDB dump file which could execute shell commands from the MariaDB client.
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We say: Put your AI vectors into your RDBMS …
Relational databases are where AI data belongs. Users need their vectors along with the rest of their data, in a standard database which offers performance, scalability, and all the other traditional virtues, such as ACID compliance.
This is why we are developing MariaDB Vector. Expect to see a first preview release later this month.
… but don’t take our word for it – ask Amazon!
Now, we’re not alone in advocating the above logic. That’s probably because the logic makes sense. The best articulation of the logic of “you want your Gen AI integrated in your relational database” I’ve heard is by MariaDB Foundation Board Member Sirish Chandrasekharan, General Manager of Amazon Relational Database Services.
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What a FOSDEM weekend in Brussels! This was MariaDB Foundation’s best FOSDEM ever, although it wasn’t a FOSDEM at all. Confused? Stay tuned.
A live migration from MySQL 5.7
The highlight in several respects was the live migration of the Cantamen cluster from MySQL 5.7 to MariaDB 10.11.
Currently, cantamen operates a MySQL 5.7 master-slave-replication cluster as backbone for our Carsharing system software solution “EBuS”. We are the leading provider in this market serving some 10.000 vehicles for roughly estimated 150.000 users. Three database schemas with some 550 tables fill about 412 GB of hard disk space on the 128-GB-RAM-equipped servers.
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In this blog we will explore how to setup a docker compose file in order to migrate from MySQL 5.7 to the latest MariaDB.
In the next blog we will explain how to setup a docker compose file to migrate from MySQL 8.0 to MariaDB.
The steps to migrate from MySQL 5.7 to MariaDB are:
- Start container by running docker-compose file
- Use the MySQL data directory and start MariaDB with MARIADB_AUTO_UPGRADE=1
Let’s explore each step.
1. Start MySQL
The MySQL container is started using the following docker-compose file.
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