 to talk about is what's different about Vertica. What impressed me when we met on the plane is you shared with me, you know, your guy's dogma in a way. I mean, you have a really solid philosophy around what the right direction is. And I mentioned Stonebreaker. He obviously was pretty influential in that direction. But talk a little bit about your perspectives around your fundamental architecture. Yeah. So when the company was founded in 2005, we saw the data tsunami that was happening. And on the one hand, you look at a data cager of 40%, but you look at IT budgets that are growing between 2% and 5%. And that was true back then. It's probably even more true now. So something has to give. You can't have that much information with budgets the way they are. Meanwhile, most of the traditional database technologies that were out there, they were created for OLTP environments, transactional environments. They weren't created for analytics. So the premise of Vertica was to design something from scratch, a purpose-built analytic platform that can handle both the volume of data, the real-time nature of analytics, and the scale of big data. And we wanted to make it sort of big data for the masses, something that's very simple for not just programmers and PhDs to be able to work with, but really for anybody that's been trained with SQL, leverage this platform, but also fix a lot of the inherent issues with traditional relational technology around scalability, around flexibility. So we put together a platform that I think is very unique when compared to a lot of the other database platforms out there. And so it was primarily SQL-based for the first four versions. And then in 5.0, we introduced a software development kit, and we support procedural programming that leverages the parallelism of our platform. But again, all of that is handled automatically, the compression is automatic, so you don't have to deal with a lot of the hand coding that you might on some other type of platform.