Inside MySQL: Sakila Speaks Podcast Por Oracle Corporation arte de portada

Inside MySQL: Sakila Speaks

Inside MySQL: Sakila Speaks

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The Inside MySQL, Sakila Speaks podcast is dedicated to all things MySQL. We bring you the latest news from the MySQL team, MySQL product updates, and inciteful interviews with members of the MySQL Community. Sit back and enjoy as your hosts, Fred Descamps and Scott Stroz, bring you the latest updates on your favorite open-source database.2024 Economía
Episodios
  • MyVector Magic: Elevating MySQL with AI Search

    MyVector Magic: Elevating MySQL with AI Search
    Sep 18 2025
    Oracle Ace Alkin Tezuysal joins leFred and Scott to introduce the MyVector plugin for MySQL Community Edition, bringing powerful vector search capabilities to your favorite open-source database. Learn how MyVector enables advanced AI and similarity search features, why this matters for modern applications, and how the MySQL community can easily get started. ------------------------------------------------------------- Episode Transcript: 00:00.000 --> 00:25.000 Welcome to Inside MySQL: Sakila Speaks, a podcast dedicated to all things MySQL. We bring you the latest news from the MySQL team, MySQL product updates and insightful interviews with members of the MySQL community. 00:25.000 --> 00:32.000 Sit back and enjoy as your hosts bring you the latest updates on your favorite open source database. Let's get started. 00:32.000 --> 00:37.000 Hello and welcome to Sakila Speaks, the podcast dedicated to MySQL. I'm LeFred. 00:37.000 --> 00:38.000 And I'm Scott Stroz. 00:38.000 --> 00:47.000 Joining us today is Alkin Tezuysal. We know each other for a long time already and Alkin serves as Director of Services at Altinity Inc. 00:47.000 --> 00:55.000 Bringing over 30 years of experience in open source relational databases with deep expertise in MySQL, of course, and ClickHouse. 00:55.000 --> 01:08.000 He co-authored key references works including MySQL Cookbook 4th edition that came in 2022 and Database Design and Modeling with Postgres and MySQL in 2024. 01:08.000 --> 01:21.000 Alkin, you have been honored as MySQL Rockstar in 2023. And since this year, you are also an Oracle Ace Pro for MySQL. Congratulations and welcome to Inside MySQL: Sakila Speaks. 01:21.000 --> 01:23.000 Thank you very much, everyone. 01:23.000 --> 01:34.000 We're glad you're here. Alkin, as you may not know, this season of the podcast is dedicated to all things AI as it relates to MySQL and HeatWave. 01:34.000 --> 01:43.000 And you actually created or wrote a plugin for MySQL Community that kind of helped with that, MyVector. 01:43.000 --> 01:48.000 Can you give us an overview of what MyVector is and what problem it's meant to solve? 01:48.000 --> 01:50.000 Sure. Thank you very much for the question. 01:50.000 --> 02:00.000 And I'm very happy that this year of AI and HeatWave, everything that actually contributes to this technology because it's fairly new. 02:00.000 --> 02:06.000 It's been developing for many years, as we already know, but now it's in our hands. 02:06.000 --> 02:16.000 We can use it. We can definitely use it on our day-to-day activities, whether it's troubleshooting your dishwasher or your washing machine. 02:16.000 --> 02:20.000 But we could also use it in a business-wise database. 02:20.000 --> 02:29.000 So one correction I want to make is I am a contributor to MyVector plugin, not to author. 02:29.000 --> 02:34.000 The author is Shankar Iyer, and he's a developer for databases for many years. 02:34.000 --> 02:40.000 He's got a lot of experience where I've actually been presenting and supporting this project. 02:40.000 --> 02:49.000 And that's the small correction. Other than that, MyVector is a native plugin for MySQL that adds support for storing and searching high dimensional vectors. 02:49.000 --> 02:55.000 This is basically a very, in simple terms, what it does. 02:55.000 --> 03:00.000 And this has been in development for some time. 03:00.000 --> 03:14.000 And as we have seen other, you know, databases, other open source databases also went into this with the, you know, launching of AI to our, you know, end users. 03:14.000 --> 03:24.000 Adding approximate nearest neighbor n-search directly in SQL within MySQL database was kind of needed. 03:24.000 --> 03:29.000 And there has been similar implementations with MySQL. 03:29.000 --> 03:33.000 But MyVector is the open source version of that as a plugin. 03:33.000 --> 03:39.000 So just to wrap up that answer is MyVector column type for embedding storage. 03:39.000 --> 03:41.000 And there's a MyVector. 03:41.000 --> 03:46.000 There's a bunch of functions that MyVector distance for the similarity competition. 03:46.000 --> 03:50.000 Of course, it uses HNSW-based index algorithm, which is very popular. 03:50.000 --> 03:52.000 There's a white paper around it. 03:52.000 --> 04:01.000 It's not a rocket science or just something that was invented for MyVector that is known science. 04:01.000 --> 04:06.000 And basically, it provides an SQL native interface within MySQL. 04:06.000 --> 04:08.000 Hope that answers that question. 04:08.000 --> 04:10.000 Thank you very much, Alkin, yeah. 04:10.000 --> 04:22.000 It answers everything and very happy that you also, let's say, talk about the author that we already met also in Belgium recently. 04:22.000 --> 04:31.000 So I would like to ask you, so why is it important to have this similarity search indexes in MySQL then? 04:31.000 --> 04:40.000 Yeah. So again, going back to the AI-driven application, semantic search, product ...
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    19 m
  • Homegrown Intelligence: AI Features for On-Prem MySQL Enterprise

    Homegrown Intelligence: AI Features for On-Prem MySQL Enterprise
    Sep 4 2025
    leFred and Scott sit down with Gaurav Chadha to explore MySQL AI, a new solution that brings advanced AI features available in HeatWave to organizations running MySQL Enterprise Edition on-premises. Discover how MySQL AI bridges the gap between cloud innovation and on-premise infrastructure, making transformative AI capabilities more accessible, secure, and efficient for teams that rely on MySQL Enterprise Edition wherever their databases reside. -------------------------------------------------------------- Episode Transcript: 00:00.000 --> 00:25.000 Welcome to Inside MySQL: Sakila Speaks, a podcast dedicated to all things MySQL. We bring you the latest news from the MySQL team, MySQL product updates and insightful interviews with members of the MySQL community. 00:25.000 --> 00:32.000 Sit back and enjoy as your hosts bring you the latest updates on your favorite open source database. Let's get started. 00:32.000 --> 00:37.000 Welcome back to another episode of Inside MySQL: Sakila Speaks. Hi, I'm LeFred. 00:37.000 --> 00:38.000 And I'm Scott Stroz. 00:38.000 --> 00:41.000 Today, we are thrilled to have Guarav Chadha joining us. 00:41.000 --> 00:51.000 Guarav is a Senior Development Manager leading development of MySQL HeatWave Lakehouse with a keen interest in systems, machine learning and computer architecture. 00:51.000 --> 01:10.000 Guarav brings a multifaceted expertise to database technology. Following the completion of his PhD from the University of Michigan, Ann Arbor, Guarav started at Oracle Labs in 2016, working on a research project which eventually graduated into MySQL HeatWave. 01:10.000 --> 01:16.000 But today we will talk with him about MySQL and AI on premise. Welcome Guarav. 01:16.000 --> 01:17.000 Thanks, Fred. Hi, Scott. 01:17.000 --> 01:18.000 Hi, Guarav. How are you? 01:18.000 --> 01:19.000 Doing good. 01:19.000 --> 01:32.000 So we're going to dive right in. And AI, we see AI is taking over the world. It's being touted for the solution to everything. 01:32.000 --> 01:41.000 How do you see AI transforming traditional on-premise database environments, especially in enterprise setups? 01:41.000 --> 01:54.000 Yes, Scott. So, I completely agree. AI is a transformational technology, and it has the potential to improve everything that we see around us. 01:54.000 --> 02:07.000 So, with regards to traditional on-premise database environments, especially in enterprise setups, I see multiple categories here. So, AI is a technology and a toolset. 02:07.000 --> 02:32.000 And like many other operators in databases, it can help with more and different data analysis. So, think of AI as a new set of SQL operators, which can tease out or analyze data and derive insights that are hard to do it with other operators, with other analysis tools. 02:32.000 --> 02:45.000 And hard for folks to call up. And hard for folks to code up. And that's where I think AI enhances it very easily enters into the database environments. 02:45.000 --> 02:56.000 What I mean by that is examples are recommendation systems, anomaly detection, so on and so forth. 02:56.000 --> 03:02.000 The other category is what I would say user assistance. 03:02.000 --> 03:15.000 So, not everyone is a SQL expert. And we want database technology and databases to be accessible to more people who may or may not come from a traditional database background. 03:15.000 --> 03:22.000 And SQL is a very powerful language and where it can be daunting to start with. 03:22.000 --> 03:35.000 So, again, this is a general category where maybe folks who are not very familiar with a specific programming language like SQL could write things out in just plain natural text. 03:35.000 --> 03:42.000 And AI tools could translate this into a programmatic interface or programmatic language or SQL directly. 03:42.000 --> 03:50.000 And that's another facet where I think AI can make database systems more approachable to a larger category of folks. 03:50.000 --> 03:57.000 It can also give you more user friendly responses, like instead of saying, oh, here's the error code, something went wrong. 03:57.000 --> 04:00.000 It can give you more information, more user friendly responses. 04:00.000 --> 04:06.000 So those are some examples of where I would say the second category, user assistance. 04:06.000 --> 04:12.000 The third category of where AI could help is database management. 04:12.000 --> 04:21.000 So databases are systems of record, the sources of truth and have a very high bar of staying up and being available. 04:21.000 --> 04:30.000 AI can help schedule maintenance at the right time where maybe the workload is low. 04:30.000 --> 04:35.000 They can predict things that might get slow. 04:35.000 --> 04:43.000 We have a whole area called predictive maintenance and make databases more highly available, more easily approachable. 04:43.000 --> 04:44.000 Thank you. 04:44.000 --> 04:46.000 This sounds very interesting. 04:46.000 --> 04:50.000 And because we are talking ...
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    20 m
  • Let HeatWave Drive: The AutoPilot Advantage

    Let HeatWave Drive: The AutoPilot Advantage
    Aug 21 2025
    In this episode, leFred and Scott are joined by Onur Kocberber to explore the many features of HeatWave AutoPilot. Learn how AutoPilot’s intelligent automation helps manage MySQL instances with ease, optimizes performance, and reduces operational costs. Onur shares practical insights and real-world examples showing how customers can streamline their database operations with HeatWave AutoPilot. ------------------------------------------------------------- Episode Transcript: 00:00:00:00 - 00:00:31:20 Welcome to Inside MySQL: Sakila Speaks. A podcast dedicated to all things MySQL. We bring you the latest news from the MySQL team, MySQL project updates and insightful interviews with members of the MySQL community. Sit back and enjoy as your hosts bring you the latest updates on your favorite open source database. Let's get started! 00:00:31:22 - 00:01:03:00 Hello and welcome to Sakila Speaks, the podcast dedicated to MySQL. I am leFred and I'm Scott Stroz, joining us today is Onur Kocberber. Onur is currently a director of Development at Oracle, leading efforts on MySQL HeatWave, specifically working on the AutoPilot. Based in Oracle's Zurich office, Onur focuses in advanced research and development to improve cloud database performance through interpretable machine learning techniques. 00:01:03:02 - 00:01:24:16 He plays a key role in the ongoing growth of HeatWave, including work on new offering like the HeatWave Lakehouse and HeatWave GenAI service. Welcome, Onur. Thanks. Thanks leFred, thanks Scott. Great to be here. So Onur, can you tell us a bit about your journey? What led you to Oracle and specifically to the MySQL HeatWave team? All right. 00:01:24:16 - 00:01:53:10 So I, I was a grad student at EPFL Lausanne in Switzerland, and, I was doing research specific doing database, accelerators, both for, with hardware and software. And, at the time, I knew that Oracle Labs had a very exciting project about, building basically hardware, software, core design, database machines. And once I graduated, I knew that there were really good set of people. 00:01:53:10 - 00:02:21:18 And that's, how I joined. So I came to basically Zurich, to to the Oracle Labs branch. And then eventually, maybe fast forward ten years, we have, HeatWave database service, but, what we see includes MySQL and other things I will discuss today. That is fantastic. So, Onur, this entire season has been dedicated to, everything AI. 00:02:21:18 - 00:02:47:07 What AI offerings that HeatWave has and some of our listeners, I would guess maybe many of our listeners probably aren't too familiar with, HeatWave AutoPilot. Can you give us a high altitude overview of what AutoPilot is and, what problems that might be resolved? So the database systems today are all cloud databases, right? And, these are many services. 00:02:47:07 - 00:03:21:04 And the onus is on us, in terms of managing these systems. So the customers are expecting basically a full, full fledged, automated service with no, let's say rough edges. And that's where, AutoPilot, comes into play. And when we started the project, when, MySQL HeatWave was becoming a cloud service, we, also started the AutoPilot project, and, we basically targeted four different, let's say, problem domains. 00:03:21:04 - 00:03:53:04 So these are, setting up the system, data, basically loading the data or data management query execution and then failure handling. And, for each of these, categories, we basically looked at what, how we could, improve customer experience as well as customer performance. And at the same time, we put the machine learning, as one of our, basically main objectives because, this is a very old topic, right? 00:03:53:04 - 00:04:18:12 This is this is not a new topic like database management on automatic database, admins and DBAs and such. So that's why we took all the, academic research, plus the realities all today, which is the cloud services. And then, we looked at these four different pillars and then fast forward to today, we have like a double digit numbers in the AutoPilot suite. 00:04:18:14 - 00:04:55:12 Wonderful. And that's awesome. So and why then, this HeatWave AutoPilot is a game changer for users. Right. So, one of the things that we were seeing in the early days of our services that customers would sometimes put together, let's say, scripts or rules or let's say, some sort of, business practices, right? And in AutoPilot, we are taking all of those, especially what you're observing or what you're anticipating, right, that, the customers will have problems with. 00:04:55:16 - 00:05:18:07 And then we are offering them out-of-the-box ready to use for the for the customers. Some of those are fully automated, like, let's say, for or planned improvements. These are like these are happening completely transparent to the use it and some of the features that are a bit more about, the cost optimization of the service or performance optimizations are provided as an advisor. 00:05:...
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    27 m
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