Category Archives: Vectors
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!”
Today, we are excited to announce a new fund to help give MariaDB Vector a high-quality integration into as many LLM frameworks as possible. This means that you can get rewarded for integrating MariaDB Vector into a known framework! This program will run until the end of February 2025.
How it will work
- Pick a framework: You need to pick one of the frameworks from the list curated by Qdrant that you would like to work on adding MariaDB Vector support to.
- Contact us: Contact us on the MariaDB Zulip, in the General channel, just create a topic.
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Continue reading “Announcing the MariaDB Vector Bounty Program!”
As you have probably seen in earlier posts, the preview version of MariaDB Vector is out and ready for you to play with. We have had input from several different places during the development of this feature. This, of course, includes hardware manufacturers such as Intel.
In the background, Intel have been prototyping using AVX512 instructions for dot product and bloom filter. Both of these are functions are part of vector searches. If you haven’t heard of these terms, let me try and break them down.
AVX-512 – 512-bit extensions to the Intel Advanced Vector Extension
The AVX512 instructions themselves are CPU specific instructions that are designed to run calculations on large vectors of numbers simultaneously.
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Continue reading “Intel improving the performance of MariaDB Vector”
Come join us in Berlin, on Tue 17 Sep 2024! It’s time for our next MariaDB Server Fest, which we invite you to enjoy in person or virtually.
MariaDB Server Fests are the events where MariaDB Foundation and friends celebrate and share the latest new happenings in the world of MariaDB Server. And Berlin is a great place to be – to work in, to travel to, to meet in.
Welcome to Berlin!
The physical event is hosted by MariaDB Foundation’s valued sponsor IONOS, on Revaler Straße 30 in the vibrant and trendy Friedrichshain area of Berlin.
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MariaDB Vector preview was recently released, bringing much awaited Vector Search functionality to MariaDB Server. One of the major open source contributors to MariaDB Vector has been Amazon. To share the excitement and get an inside view about what it’s like to contribute to MariaDB Server, I had a chat with software engineer Hugo Wen on the Amazon RDS team.
Hugo’s contributions to MariaDB Vector
Hugo Wen’s work on vector similarity search in MariaDB and MySQL started when Amazon’s leadership identified Vector Search functionality as a critical addition and decided to invest Amazon RDS team’s time on contributing to MariaDB Vector.
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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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AI was everywhere at Intel Vision this week in London. Nearly every keynote and breakout presentation was centred around AI. I had the honour of being interviewed by Intel’s jovial Chief Commercial Officer Christoph Schell, who is just about as stereotypically German as his former neighbour from Stuttgart Jürgen Klopp (whom he referenced on-stage), namely: not at all.
Staying German but perhaps a tad less Klopp-like, Thomas Bach was one of many interviewed on-stage by Christoph. The president of the International Olympic Committee nevertheless impressed me by his quick-witted reply to Christoph’s question as to how AI would have made an impact if it had been in place during Thomas Bach’s fencing career.
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Continue reading “MariaDB Vector at Intel Vision – AI Everywhere”
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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