DoorDash has about 35 million users, and there is zero interaction between users. The median user uses doordash maybe once a week. So 5 million sessions a day, all happening in the same 3 hour window. That's 2 million sessions per hour at peak times.

How does DoorDash get to 1.2 million queries per second. 1.2mqps * 10000 seconds in 3 hours = 12 billion queries to process 5 million orders? That's wild. Is it all analytics? This is highly suspect. 35m users isn't nothing, but it isn't exactly Facebook scale either.

> About 1.2 million queries per second at daily peak hours.

> About 2,300 total nodes spread across 300+ clusters.

> About 1.9 petabytes of data on disk.

> Close to 900 changefeeds.

> Largest cluster is currently 280 TB in size (but has peaked above 600 TB), with a single table that is 122 TB.

all of this yet my food still arrives cold af

kidding aside, I wonder if DD has the same problems as Uber or Lyft except with food delivery. Each new "change feed" is a specific region, county/municipality, or city. Federal, state, and local laws all handled delicately.

I'm not really seeing why DoorDash needs all their operational data in one monster clustered database. I would think its so much simpler to shard the data by region for operational queries and aggregate in the background for long-term storage.

Ha! Amazing (didn’t know this was being written or put up).

This is a summary of a recent conference talk:

https://youtu.be/jCjrfpF64Kc?si=Gf-gp_ixX2V6Qz8V

This was my team. We did and lived this. AMA.

Do you know what DoorDash doesn’t manage? A staging/test environment. All testing for API integrations is done in prod on shared account. The docs and the API endpoints themselves leave a lot to be desired as well.

interesting. curious if anyone has benchmarked it relative to other dbs. like: https://benchmark.clickhouse.com/

This reads like a long form advertisement.