What are the current trends driving the increase in adoption of cloud warehouses beyond the impact of COVID-19?

Data warehouses all got started around 2012, 2013, 2014. The phrase "big data" peaked as a concept in 2014 and petered out from there. Partially because I think the generation of tools that were powering that -- like the Hadoops of the world -- everybody realized, "Oh, this is a huge pain in the butt to manage." Cloud data warehouses were giving you a lot of that scale but with a SQL interface, as opposed to having to learn a whole new processing language or that sort of thing.

I think that is a really interesting trend here. Redshift is ultimately a Postgres version or was started as a special extension to Postgres. Snowflake speaks a very well designed dialect of SQL. One of the things that the cloud data warehouses do, but don't necessarily get credit for, is go back to plain old SQL that everybody understood. So one of the interesting trends of describing adoption here is abandoning the sense that "I need to have big data in order to justify building this infrastructure."

We're seeing the modern data stack being adopted at much earlier startups now, because it's easier to turn these things on. For the most part, it's credit card swipes. You can plug them in, they all talk SQL to each other. You can mix and match them a little bit. It's a lot easier to walk up to a modern data stack than it was four, five or six years ago where it still probably involved a lot of, "Okay, I'm going to get it running, but then I've probably got the phrase EC2 in here somewhere, and I need to start managing some infrastructure in order to get this to do what I actually want."

A lot of this is becoming very turnkey now. Census is a part of that. Like I mentioned before, our biggest competitor is the engineering teams that were building custom integrations. The nice thing about that is they really hate maintaining those custom integrations. They're not big fans of the Salesforce API -- they have some nice things to say about it, but this is not their day job, and it's not what they want to spend their time doing.

We're taking some of the patterns that five years ago would have had to have been cobbled together through open-source projects and custom code, and now making them something that you don't need an engineer to get. You don't even need the engineer to do the work in Census. You can have your marketing team use it. You can have anybody use it. I think that's largely true for the modern data stack overall. It's not this "only big company" thing by virtue of the size of the data or the size of your data team. This is something that smaller companies or roles that are not necessarily data can get started using.