Tag Archives: MariaDB
MariaDB Foundation is pleased to welcome Continuent as a new Silver Sponsor.
Continuent develops solutions for organizations running business-critical applications on MariaDB and other MySQL-compatible databases. Its flagship product, Tungsten Cluster, helps organizations manage database availability, disaster recovery and distributed deployments across on-premises, cloud and hybrid environments.
The company has worked with open-source database technologies for more than two decades and brings extensive experience from demanding production environments across SaaS, financial services, telecommunications, e-commerce and other industries.
“Continuent has a long history in the MariaDB and wider open-source database ecosystem.
…
Continue reading “Continuent joins MariaDB Foundation as a Silver Sponsor”
MariaDB Foundation is pleased to announce that Passbolt has renewed its Silver sponsorship for another year, continuing its long-term support for the MariaDB open-source ecosystem.
Passbolt is an open-source password manager designed for teams, with a strong focus on security, privacy, and user control. Its continued support reflects a shared commitment to building practical, trustworthy open-source infrastructure that organizations can deploy and operate with confidence.
Building on the Privacy-First Stack
During the first year of collaboration, Passbolt became part of the Privacy-First Solution Stack alongside Nextcloud and MariaDB Server.
…
Continue reading “Passbolt renews its support for MariaDB Foundation”
Tracking down changes in database performance is one of the hardest parts of engineering, especially when the change is buried somewhere in a long commit history.
To make this work easier and more repeatable, I put together a small but important tool:
This script does one thing well:
Given a commit hash, it checks out that commit, builds it cleanly, and packages it in a deterministic way so the Test Automation Framework (TAF) can run consistent performance tests.
Why this matters
- When you are bisecting or doing a manual binary search across hundreds of commits, you need reproducible builds.
…
Continue reading “Simple tool to build MariaDB commits for performance-change analysis”
An early look at the DuckDB storage engine for MariaDB — columnar, vectorized analytics that live right next to your transactional tables.
The problem
MariaDB’s InnoDB is excellent at what it was built for: transactions. Row-by-row inserts, updates, point lookups, strong consistency. But the moment you ask it to scan tens of millions of rows for a multi-way join with a few aggregations, a row store has to work hard.
The usual answer is to stand up a separate analytical system, then build ETL pipelines to copy data into it.
…
Continue reading “DuckDB Storage Engine for MariaDB. When the Sea Lion Learns to Quack.”
Inspired by some recent LinkedIn posts, I decided to take the AI in my own hands and do some stats on the MariaDB and MySQL repositories.
This graph is what I’ve got.
Not only have MariaDB Server distinct contributors surpassed the distinct MySQL Server contributors count! The External MariaDB contributors alone did! *
This is how the Power Of the Community looks like!
- You get to use a more functional, performant and error free MariaDB Server
- You get a say in shaping the future of the MariaDB Server.
…
…
Continue reading “MariaDB Foundation: Bringing TPC-B Back To Life”
If you ever considered contributing code to the MariaDB server, you should know that this is an intricate process involving multiple steps and multiple actors. To help you see your contributions successfully merged into the MariaDB Server codebase I’ve compiled a comprehensive description of the contribution process itself, the roles involved into it, the sequence of actions and conditions for transition from one to another. There’s even a diagram!
Please go to COMMUNITY_CONTRIBUTIONS.md.
This of course is going to be a moving target! I fully intend to keep the document up to date and enhance it with clarifications and process changes as they happen.
…
Continue reading “Documented: The MariaDB Server (Community) Contribution Process”
In the previous parts of this series we’ve seen how MariaDB stores vector indexes in a table and how to implement HNSW for a good performance. But MariaDB is not implementing HNSW, it calls its vector search algorithm mHNWS, a modified HNSW. Let’s see how exactly it was modified.
Not so greedy!
HWNS, like many, if not most, graph based vector search algorithms is greedy. Think of it this way, when it needs to find just one nearest vector (ef=1), it will walk the graph always choosing the node that will take it the closest to the target at this particular step.
…