Jeff Kao

Same for InfluxDB.

Right.

There's so many projects around there and so much community backing that we felt it was such a mature project that we could use it for our purposes.

I know for sure there are a lot of like Rust crates now.

Things like, I believe, SLED, stuff like that.

There's many people who write, you know, these sort of embedded databases.

And essentially, RocksDB is this data structure called a log structure merge tree.

And it's really designed for high write throughput, which is sort of different from our use case.

But as like I mentioned before, technology is so cyclical where, you know, if somebody builds a database that's like high write throughput, well, they actually adopt a lot of these concepts and ways to tune it so that, you know, it's also very well tuned for read throughputs.

And so we just felt that, yeah, that, you know, community backing and the sort of it is a project that's written not in Rust.

Right.

So that was sort of another nice thing.

We had all the Rust bindings to RocksDB and it was very simple, like integration to be able to just pull in that project.

And that is our sort of primary storage layer for, you know, all of our entities.

So addresses, places, and different regions.

And so it serves, you know, a number of different purposes.

So obviously like primary key fetches.

So when our services have, say, like an event and they have an ID for a place, they'll fetch, you know, that from our service.

But we also...

index it in a way that makes it really easy to do geo lookups.