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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 Ökonomie
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  • 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 Korcerber 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 Min.
  • HeatWave Hot Takes: The Power of ML and GenAI

    HeatWave Hot Takes: The Power of ML and GenAI
    Aug 7 2025
    In this episode, leFred and Scott welcome Jayant Sharma and Sanjay Jinturkar to the Sakila Studio for an insightful conversation on machine learning and generative AI within HeatWave. Discover how these cutting-edge technologies are integrated, what makes HeatWave unique, and how organizations can leverage its capabilities to unlock new possibilities in data and AI. Tune in for practical insights, real-world use cases, and a closer look at the future of analytics. ------------------------------------------------------------ Episode Transcript: 00:00:00:00 - 00:00:32:01 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! 00:00:32:03 - 00:00:54:17 Hello and welcome to Sakila Speaks, the podcast dedicated to MySQL. I am leFred and I'm Scott Stroz. Today for the second episode of season three dedicated on AI. I am pleased to welcome Sanjay Jinturkar. Sorry if I pronounce it badly. No, you did it right. Hi there. Thank you. So Sanjay is the senior director at Oracle based in New Jersey. 00:00:54:19 - 00:01:21:13 He leads product development for it with AutoML and GenAI with a strong focus on integrating these technologies directly into each HeatWave database. And Sanjay has been instrumental in enhancing HeatWave's machine learning and GenAI tool sets, enabling use case like predictive maintenance, fraud detection and intelligent dicument and Q&A. And also we have a second guest today. 00:01:21:13 - 00:01:48:21 It's a Jayant Sharma. Hi, Jayant. Hello. So Jayant Sharma is senior director of product management at Oracle. He has over 20 years of experience in databases, spatial analytics and application development. He's currently focused on the product strategy and design of the Heatwave MySQL managed services offering. Hey Fred. Thank you, both of you for joining us today. So I'm going to dive right in with the question for Jayant. 00:01:48:23 - 00:02:12:14 Why did Oracle decide to integrate machine learning in generative AI capabilities directly into HeatWave? Thank you Scott, first for this opportunity. And yes, we have to start with first, you know, talking about MySQL, right? MySQL is the world's most popular open source database. And what do all of these customers, the thousands of customers that they have, do with it? 00:02:12:16 - 00:02:47:05 They manage a business process. They manage their enterprise, right? Their focus is on what they want to do, why they want to do it, and not so much the how. That's what MySQL makes it easier. And Heatwave is a managed service on MySQL. Okay, so as folks are modernizing their applications, taking advantage of new technology, they want to be able to use new workloads, new analytics, and modernize their business processes, make it more efficient, make it more effective. 00:02:47:07 - 00:03:09:17 In order to do that, they want to do things such as machine learning and use the benefits of generative AI. However, what they want to focus on, as we said, is what they want, why they want to do it and not the how. So they don't want to have to think about. I have all of this data that's potentially a goldmine. 00:03:09:19 - 00:03:40:07 How do I extract nuggets from it, and how do I safely move it and transfer in between the best of breed tools? I want to be able to do things where they are. I want to bring the capabilities, these new capabilities to my data. I don't want to take my data to where those capabilities are exposed, right? That is why we made it possible to do machine learning and GenAI where your gold mine is, where your data is in MySQL in Heatwave. 00:03:40:09 - 00:04:06:07 Awesome. Thank you. So, I would like to ask you to Sanjay, then. How Do the the, machine learning engine in the HeatWave, offer differ from, using external machine learning pipelines with the with the data we have in the database? It differs in a couple of weeks, specifically how the models are built, who builds them and where they are built. 00:04:06:09 - 00:04:46:09 So our pipeline, we provide, automated pipeline, which can take your data in MySQL database or Lakehouse, and then automatically generate the model for you. So it does the, usual tasks of pre-processing, hyperparameter optimization, and, data cleansing, etc. automatically so that the user doesn't have to do that. We would even go ahead and do, explanations for you in certain use cases, given that this is automated, a big side effect of that is users don't need to be experts in machine learning. 00:04:46:11 - 00:05:16:08 What they need to focus on is their business problem, and how that business problem maps onto one of the features that we provide. From there onwards, the pipeline takes over and generates the models for it. And the third piece ...
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    27 Min.
  • AI for the Rest of Us: A High-Level Overview

    AI for the Rest of Us: A High-Level Overview
    Jul 25 2025
    Kick off Season 3 of Inside MySQL: Sakila Speaks as leFred and Scott welcome Matt Quinn for an engaging introduction to the world of Artificial Intelligence. In this episode, we step back from the database and explore what AI really is, how it’s shaping society and technology, and why it matters to anyone in tech today. Whether you’re just curious about AI or eager to understand its key concepts, join us as we break down the basics and set the stage for a season of discovery. ------------------------------------------------------------ Episode Transcript: 00:00:00:00 - 00:00:31:22 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! 00:00:32:00 - 00:00:58:22 Hello and welcome to Sakila Speaks, the podcast dedicated to MySQL. I am leFred and I'm Scott Stroz. Join us today. It's Matt Quinn, vice president and head of AI at Orracle. Matt leads how Oracle Cloud Infrastructure's AI services are adopted by customers in EMEA. Matt brings deep expertise in enterprise software strategy and a passion for making AI both powerful and its adoption practical. 00:00:59:00 - 00:01:21:03 Today he is here to help us unpack what GenAI really means for the organizations we work for and buy from, and what it means for developers, data professionals, and MySQL users everywhere. Matt, welcome to Inside MySQL: Sakila Speaks. It's great to have you with us to kick off season three of our podcast. Thank you very much, Fred, Scott, great to be with you. 00:01:21:08 - 00:01:43:21 Looking forward to, to an interesting conversation and getting us going for season three. Awesome. Matt, thanks for being here with us. So right off the bat, when most people hear the term AI, they probably think of chat bots. But that's just one form of AI. Can you help provide us with like a high overview of the different types of AI that exist? 00:01:43:23 - 00:02:15:10 Absolutely. And I think AI and itself is a broad church, right? There's a number of different, kinds of AI. The term actually dates back to the 1950s as a concept for you know, machine thinking. It's had a couple of false dawns over the time when compute and data to train. I wasn't really quite ready for this, but as we got into the 90s and the early noughties, as compute power grew, as storage grew, a confluence of internet accessibility, lots of data becoming available, and then we time fed forward. 00:02:15:12 - 00:02:33:12 We found that organizations could do the fundamentals of what we know of AI today things like machine learning. So learning a trend and a pattern, looking at what happened in the past and do a statistical regression on that to predict some future outcome based on what happened in the past. And we use examples of this today without even knowing it. 00:02:33:12 - 00:02:52:11 You know, is this email that's coming into my email system, is this spam or not spam? Those kind to classifier types of AI have been prevalent for the last ten, 15, 20 years, and we're moving forward to where AI has this more kind of human interaction. It's surfacing and it's suddenly popped into the zeitgeist, for for conversation. 00:02:52:15 - 00:03:14:03 So it has multiple facets. We have machine learning trained something to do, something very specific, show it, something that it's seen before and enable it to predict the future based on what it's learned. But we're starting to see this wave of generative AI do more advanced, more nuanced, more humanlike things, and I think that's a really powerful kind of inflection point that we've seen in the last two, three years. 00:03:14:05 - 00:03:39:02 Thank you. So because in your first, answer, you said you said about the 70s and 90s, but why is I having such a huge moment right now? So what changed since that time? I think that the real inflection point is the the kind of conversational nature of it. You can speak human to it, and it can speak human back to you. 00:03:39:04 - 00:04:01:13 If I think about how compute evolved, you know, it used to be I had to type cryptic commands on the green screen in order to be able to use a computer, which meant the audience of people who could use computer to do something was very limited. In the 80s is the GUI. The graphical user interface kind of emerged suddenly it was a keyboard in a mouse, and the population of people who could interact with the computer was much broader. 00:04:01:15 - 00:04:19:02 Mobile did the same for us, but you still had to learn things. You had to take the human to interact in a way that made sense to the computer. With generative AI, I think what's happened in the last 2 or 3 years is actually the computer is coming to meet the human. Suddenly it's able to interact with us in our language. 00:04:...
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    27 Min.
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