What Is LTAP? Lakebase + Genie Explained by Databricks CTO

Yeah, thanks, guys. Thanks for having me on.

Yeah, it's definitely been a great year for launches and a lot of things coming together. I think there's two really big ones. I think the first one is Genie. It's gotten so good now at actually understanding many types of business data and many types of questions. In particular, you can add unstructured data too now, like your documents in SharePoint or Google Drive or anything like that. And when you start to use that together with your business data that's in tables, and it also has the ability to create charts and reports and stuff for you, it becomes a very, very powerful co-worker. So I'm really excited about that. I use that all the time just in my normal job to figure out what's going on and to make plans and things. It's great to get it into more people's hands and make it really work well in different domains. So I think that's very transformative. In a few years, that might be the main interface for working with any data, and even writing code and jobs on the platform. And then the other thing, it's more sort of in the technical details, but maybe even more interesting in some ways, I think is LTAP, which is letting you have your lakehouse Postgres and your analytics Spark engine on a single copy of the data. It looks like native Postgres for the online apps, it performs like that, but you can also analyze the data as events are happening. We remove so many complicated systems and delays in building an application end-to-end. It will actually reduce overall the cost of hosting these apps and let you understand much better what they're doing. We're very excited by how well it's really performing and how we can basically turn it on for pretty much everything.

Yeah, and in general, I think with AI and with other technologies, it basically makes data more useful, right, because you can make more decisions on it automatically and make better ones. So that means having really timely data that you can then feed into these things is even more important. Before, if you got data very quickly but it was text or something, you need a human to look at it. So there's no point getting it instantly; just get it every night or whatever, take a look, and see what's going on. But now you can have an agent look at it. So you could get it immediately and realize this customer is unhappy or something and we need to do something, and actually take a good action about that. So I think a lot of the infrastructure will have to change. And if you look at it with LTAP and with ZeroBus as well, you can have basically a single table, a single data store that supports online Postgres transactions, supports streaming records into it, and supports analytics. It's sort of a single copy of the data that does all those things, and it's immediately visible to all those use cases.