pgx

I'm also confused. 2. Agreed. 150 ms is extraordinarily slow for a point lookup from a single table. A simple lookup should take around 1 ms since it'll be cached in memory. 3. Also agreed. The actual database time looks to be the first flame. Hovering over it shows PG::Connection::exec which accounts for 2.5% of the time. I was curious about date parsing and dug up the source [1]. Seems like you could gain a ton of speed back by using a postgres specific timestamp parsing routine. In Go, it's 40 lines [2] [1] https://github.com/ruby/date/blob/d21c69450a57a1931ab6190385... [2]: https://github.com/jackc/pgx/blob/a968ce3437eefc4168b39bbc4b...

Awesome to hear more about MySQL/Vitess connection pooling. Folks typically only consider memory usage for database connections, but we've also had to consider the p99 latency for establishing a connection. For SpiceDB[0] one place we've struggled for our MySQL backend (originally contributed by GitHub who are big Vitess users) is preemptively establishing connections in the pool so that it's always full. PGX[1] has been fantastic for Postgres and CockroachDB, but I haven't found something with enough control for MySQL. PS: Lots of love to to all my friends at Planetscale! SpiceDB is also a big user of vtprotobuf[2] -- a great contribution to the Go gRPC ecosystem. [0]: https://github.com/authzed/spicedb [1]: https://github.com/jackc/pgx [2]: https://github.com/planetscale/vtprotobuf