Category: AI & Vector
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MariaDB Vector: How it works
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 […]
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Big Vector Search Benchmark: 10 databases comparison
I have benchmarked MariaDB Vector before, but it was a while ago. Users kept asking about Milvus. New pgvector alternatives were gaining popularity. And I simply wanted to see if MariaDB got any better. This benchmark round includes more databases, larger dataset, and no irrelevant datasets that only add noise but don’t really help today in 2026.
Dataset
Now is the AI time. Vector search is used for embeddings generated by LLMs. Most ann-benchmarks datasets are pre-AI and use, for […]
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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 […]
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BangPypers x MariaDB Python Hackathon – Winners Announced!
Last Saturday marked an exciting milestone: the announcement of the winners in our first large-scale MariaDB Python Hackathon, organised in collaboration with BangPypers, HackerEarth, and MariaDB plc. Over the past months, developers from across India have explored new ways to make MariaDB easier to use, more connected, and better integrated into today’s most important open-source ecosystems.
This post celebrates the outstanding contributions in both the Integration Track — projects that help MariaDB work seamlessly with other tools and frameworks – and […]
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MariaDB and AI: Building the Bridge That Really Matters
Not what AI can do for MariaDB – but what MariaDB can do for AI
I have hinted at this before (This Month in MariaDB – August 2025), but it deserves to be said again: our vision for MariaDB’s role in AI is both clear and ambitious. We do not simply want to participate in the AI space – we aim to be the bridge between real-world data and modern AI systems.
Large Language Models are, at their core, vast […]
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Can you do RAG with Full Text Search in MariaDB?
We continue our blog series on learning more about users of MariaDB. Searching LinkedIn for posts about MariaDB this morning we saw an impressive confident post about using MariaDB in a RAG solution named SemantiQ. We got curious about it and reached out to the author Lorenzo Cremonese to have a chat.
Tell us about yourself Lorenzo!
I’m an Italian studying in Spain. I began programming when I was 14, and I’m now 22. I’m a self-taught web developer since […]
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MariaDB 11.8 LTS Released
Now is a good time to upgrade to the freshest MariaDB Server. MariaDB 11.8 is the yearly long term support release for 2025. It’s the first LTS with support for MariaDB Vector, and it includes a number of other updates based on user requests. You can seamlessly upgrade to MariaDB 11.8 from MariaDB 11.4 (the previous LTS) or any older release, back to MariaDB Server 10.0 or earlier, including most versions of MySQL Server.
MariaDB 11.8 LTS includes everything added […]
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Youtube Semantic Search is the winner of MariaDB AI RAG Hackathon innovation track
Last week we announced the winners of the MariaDB AI RAG hackathon that we organized together with the Helsinki Python meetup group. Now is time to go for a deep dive into the innovation track winner. Dymtro Abramov put together an end to end RAG application for making technical meetup videos searchable with semantic relevance (based on their caption texts). We were impressed by the idea and the implementation that is definitely beyond just a proof of concept for AI […]