Cofounder and Chief Architect, Databricks
Databricks Data+AI Summit 2025 Keynote | Co-founder Reynold Xin and Neon Co-founder Nikita Shamgunov
Nikita Shamgunov's presentation at the Data+AI Summit 2025 highlighted the transformative role of AI in database management, ...
About Reynold Xin
Reynold Xin, cofounder and chief architect at Databricks, has been discussing the company's recent product announcements and his views on the future of data infrastructure. At the Data + AI Summit in June 2026, Xin introduced Lakehouse//RT, a real-time analytics engine powered by a new compute engine called Reyden. He demonstrated Reyden executing 8,000 queries at 6,000 queries per second with a tail latency of 37 milliseconds, and said that "none of existing systems can do this." Xin also described Lakebase branching, a copy-on-write clone of an entire database that he said can be created in under a second and costs roughly a penny before being thrown away. He argued that traditional databases "inhibit innovation" because they are slow and expensive to provision, and that infrastructure should enable "rapid experimentation at scale cheaply." Xin has also discussed the impact of AI agents on database architecture. He stated that "agents are becoming the actual primary persona" for database usage, and that "99% of psycho value engineers these days don't write code manually and don't provision the database manually." He described Databricks' work on LTAP (lake transactional and analytical processing), which aims to unify transactional and analytical databases, and Omnigent, an open-source meta-harness for combining different coding agents. Xin said that "many of the traditional software will be sort of rewritten with this new paradigm, which is just get the data to be there and then let's slap some AGI on top."
Transcript (9 segments)
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Reynold Xin0:00
Thank you Holly and virtual handshake. So at Data and AI Summit and other conferences we announce products of various stages of maturity. Where is Lakebase? We just spent so much time talking to you about it. So in the last year we've actually been privately previewing Lakebase with hundreds of customers, and many of their logos are showing on stage here across a variety of industries. Many of them are actually running Lakebase in production. And we're also very happy to have the following launch partners joining us to announce Lakebase itself. This includes catalog vendors, BI vendors, agentic coding platforms, and consulting services. But the best part is that Lakebase is available today, right now. So not something coming next year, but today, starting today, in all of your Databricks workspaces, depending on which region you are, you can either explicitly opt-in or it's already on out of the box for you. It includes a full-blown fully managed Postgres instance, all the lakehouse integrations, multi-cloud support, HADR. All right. And there's a lot more new features coming in the coming months. So just to summarize, Lakebase offers a fully managed Postgres instance. It comes with a novel separation of storage from compute architecture, which enables the modern-day developer experience both for humans and for AI agents. And more importantly than the Lakebase product announcement, we actually feel like this is how databases should be built in the future. And our prediction is that every other database, every other transactional OLTP database, will evolve towards this architecture in the coming years. Now we cannot talk about Lakebase without talking about the Neon acquisition, because that's what powers the innovations behind Lakebase. So with that, I would actually like to invite the CEO of Neon, Nikita, onto stage to talk to us.
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Nikita2:12
Nice shirt. Thank you.
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Reynold Xin2:16
So Nikita, you started Neon together with Stas and Heiko about four years ago. At the time Neon became sort of the leading serverless Postgres company. There are a lot of other Postgres companies and all the hyperscalers have Postgres. What problem were you trying to solve?
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Nikita2:33
So we actually focused on developer experience of all things. The biggest Neon innovation is separation of storage and compute, which allows us to store data in an open format inside of the cheapest medium, cloud object stores. And you know, lakehouse. Now what does it have to do with developer experience? Well, actually a lot. The one thing that it allows you to do is to make a serverless system, and without separation of storage and compute, it's actually kind of impossible to make a system serverless, especially a system that is a traditional database like Postgres. So now you can think about a database as just being a URL. This URL is something your application interfaces with, and then according to the application, it will increase the size or decrease the size, or scale all the way to zero if you stop driving that system, which is very convenient. You don't have to think about sizing and you only pay for what you use. The other thing that we quickly realized when we put a magnifying glass over the developer experience is that developers like to integrate their systems into their developer workflow. And that's where the idea of branching came in. And again, it's only possible to deliver on branching when you branch both schema and data if you separate storage and compute. So now to do it instantly at least. And to do it instantly as well, right, we use copy-on-write for this. Copy-on-write is not a new idea, but packaging it in a way that developers can self-serve and consume was a big innovation from Neon.
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Reynold Xin4:15
Makes sense. One other thing that was very surprising to me at least is we noticed throughout the process, hey, 80% of the databases created on neon.com were created by AI agents, not humans. So AI agents actually create four times more databases. And here's a chart. It started at 30%. What's going on there? Can you tell us more about it?
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Nikita4:35
Yeah, that's right. So last year we had 30%, now we're 80%. I actually want to make a kind of a bold prediction. In a couple of years, I think 99% of all the databases on the platform will be created by AI agents. I think we're at the dawn of the AI software revolution, and every engineer is becoming an AI engineer. What this means is if it's a human, then the human is levered by modern tools such as Cursor, Windsurf, or Microsoft Copilot. But also we now are starting to have fully autonomous AI software agents that generate software, specifically partners of Databricks, Replit and Lovable, that are part of our launch partners here. They just generate apps from a prompt, and since every application needs a database, Neon is a perfect solution for that because again, database is just a URL, database has branching, and AI kind of makes mistakes, so creating those isolated environments in a safe and secure way is a big deal for those AI systems, which is really hard to do with traditional databases, impossible.
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Reynold Xin5:55
Last question. What are you most excited about now that Neon's part of Databricks? How do you see the tech coming together, even though they kind of were coming together already?
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Nikita6:05
Well, I'm excited to build the best OLTP system in the world that is fully integrated with the data and AI platform. I think analytical and OLTP systems have been separate for a very long time, and there are all these use cases that are pure analytical, pure transactional, but then there's also everything in between. So I'm excited to not only build the most scalable and efficient OLTP system in the world, but also deliver all the use cases for all of you that span the whole range between analytics and OLTP, all based on open source, all based on Elastic source.
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Reynold Xin6:48
All right, thank you Nikita. And Ali, we're gonna pass back to you.