Tag Archives: MariaDB
In the first post of this series, I’ve described how the vector index is stored in a table and how it achieves full transactional behavior and ACID properties compatible with the storage engine of the table the user created. But while the table provides persistent storage of the index, it’s in-memory part that gives it the performance. This is how it works.
Distance calculations
This is the most performance sensitive part of the HNSW. According to various estimates, distance calculations account for 80–90% of search time. And this operation time grows linearly with the vector length.
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We are pleased to announce the availability of a preview of the MariaDB 13.0 series. MariaDB 13.0 is a preview rolling release, published on 23 March 2026, and it continues the work started in 12.3 while adding a solid set of entirely new features.
And this one is interesting.
This preview release brings a nice mix of new SQL capabilities, better optimizer insight, richer metadata, and practical engine improvements. Not every feature is flashy, but many of them are exactly the kind of changes that make daily work with MariaDB smoother, clearer, and just a bit more powerful.
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You might have seen that MariaDB Vector is fast. And is getting faster. But why? How does it achieve that? And why it is said to use mHNSW (modified HNSW) algorithm? What did it modify in the conventional HNSW that all other databases are using? Let’s take it apart and analyze piece by piece.
Introduction into HNSW
This post is not a full description of HNSW, there are many HNSW descriptions online and they are good, better than what I could’ve written. I will only show the basic concepts beyond HNSW, concepts that are crucial for the rest of the post.
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I have recently completed a large project to implement a new improved binlog format for MariaDB. The result will be available shortly in the upcoming MariaDB 12.3.1 release.
In this article, I will give a short overview of the new binlog implementation. For more details, check the documentation which is in the source tree as the file Docs/replication/binlog.md, or here: https://github.com/MariaDB/server/blob/knielsen_binlog_in_engine/Docs/replication/binlog.md
EDIT: Also see Mark Callaghan’s benchmark of the new feature.
Using the new binlog
To enable the new binlog, configure the MariaDB server with binlog_storage_engine=innodb.
Additionally, the binlog must itself be enabled as usual using the option log_bin.
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Continue reading “New binlog implementation in MariaDB 12.3”
The Queen’s Seven Predictions for 2026
When Queen Isabella I of Castile agreed to fund Columbus, it was not because the idea felt daring or exciting. It was because the old routes were failing. Europe’s trade system had become expensive, fragile, and constrained, and maintaining it unchanged was no longer a neutral decision. Supporting the voyage was not an act of romance, but of governance: an acceptance that continuing as before carried greater risk than change.
Crucially, nothing collapsed overnight. Trade still flowed. Goods still arrived. But every journey became longer, costlier, and more politically exposed.
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Mirror, mirror on the wall — what do you measure when you measure us all?
Is it skill, or is it voice?
Is it code, or is it conversation?
DB-Engines is not a looking glass of perfection, but a mirror of perception — reflecting the chorus of those who search, speak, teach, compare, and build. And like every enchanted mirror, it shows not only what is, but what the world believes it sees.
MariaDB today stands firmly among the world’s top relational databases.
Not by inheritance, and not by illusion, but by the millions who use it, trust it, and shape it.
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Continue reading “Mirror, Mirror on DB-Engines: The MariaDB Story”
This blog post is based on the YouTube presentation “MariaDB vs PostgreSQL: Technical Deep Dive | Architecture, Performance & Design Trade-offs” by Manoj Vakeel, part of MariaDB Foundation’s ongoing series exploring core database design choices and how they impact modern workloads.
The goal here is not to pick a “winner,” but to provide clear architectural insight for CTOs, database engineers, and system architects making decisions in 2025 and beyond.
“Both are powerful engines — both are proven in production — but they take very different routes to get there.” — Manoj Vakeel, MariaDB plc
Why this matters
PostgreSQL and MariaDB are two of the most widely adopted open-source relational databases.
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Continue reading “MariaDB vs PostgreSQL: Understanding the Architectural Differences That Matter”
We are thrilled to welcome Scarf as a Gold Sponsor of the MariaDB Foundation!
Scarf’s commitment to improving open source distribution and visibility aligns closely with our mission to ensure the continued openness, innovation, and sustainability of MariaDB Server. As a platform that helps open-source projects understand and grow their user base, Scarf brings unique value to the ecosystem—not just through sponsorship, but through actionable insights that benefit the broader community.
For the MariaDB Foundation, understanding who uses MariaDB—and how, where, and why—is key to making better decisions. Scarf’s privacy conscious analytics help us move beyond assumptions and anecdotes, giving us real-world data to guide our outreach, improve our documentation, tailor our events, and strengthen our developer ecosystem.
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Continue reading “Scarf Joins as Gold Sponsor of the MariaDB Foundation”