[hot_gril]

The most useful thing is learning your DBMS. There's no escaping the performance and isolation quirks of each one, and there are different bonus features in each.

One interesting thing I found about Postgres that's probably true of others too, often you can manually shard INSERT (SELECT ...) operations to speed them up linearly with the number of CPU cores, even when you have like 10 joins. EXPLAIN first, find the innermost or outermost join, and kick off a separate parallel query operating on each range of rows (id >= start AND id < end). For weird reasons, I relied on this a lot for one job 6 years ago. Postgres has added parallelism in versions 10+, but it's still not this advanced afaik.

[password4321]

It would be cool to see something automating this conversion (and other similar performance workarounds) available as a first-class feature in a SQL IDE.

[hot_gril]

I ended up building jank Python-based tooling around it to sorta automate it. You select your key and it decides the ranges for you.

Wonder if it'd be useful at all for live applications or just data processing. For the former, would need to somehow execute all reads at the same MVCC version even though they're separate connections.