Homegrown Intelligence: AI Features for On-Prem MySQL Enterprise

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.

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Episode Transcript:

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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.

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Sit back and enjoy as your hosts bring you the latest updates on your favorite open source database. Let's get started.

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Welcome back to another episode of Inside MySQL: Sakila Speaks. Hi, I'm LeFred.

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And I'm Scott Stroz.

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Today, we are thrilled to have Guarav Chadha joining us.

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Guarav is a Senior Development Manager leading development of MySQL HeatWave Lakehouse with a keen interest in systems, machine learning and computer architecture.

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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.

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But today we will talk with him about MySQL and AI on premise. Welcome Guarav.

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Thanks, Fred. Hi, Scott.

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Hi, Guarav. How are you?

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Doing good.

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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.

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How do you see AI transforming traditional on-premise database environments, especially in enterprise setups?

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Yes, Scott. So, I completely agree. AI is a transformational technology, and it has the potential to improve everything that we see around us.

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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.

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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.

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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.

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What I mean by that is examples are recommendation systems, anomaly detection, so on and so forth.

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The other category is what I would say user assistance.

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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.

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And SQL is a very powerful language and where it can be daunting to start with.

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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.

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And AI tools could translate this into a programmatic interface or programmatic language or SQL directly.

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And that's another facet where I think AI can make database systems more approachable to a larger category of folks.

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It can also give you more user friendly responses, like instead of saying, oh, here's the error code, something went wrong.

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It can give you more information, more user friendly responses.

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So those are some examples of where I would say the second category, user assistance.

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The third category of where AI could help is database management.

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So databases are systems of record, the sources of truth and have a very high bar of staying up and being available.

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AI can help schedule mai