Probably not that relevant for a data team, but this is what we do as a backend team: We use Microsoft SQL's docker image and spin it up in the background on o

Probably not that relevant for a data team, but this is what we do as a backend team: We use Microsoft SQL's docker image and spin it up in the background on our laptop/CI server so port 1433 has a database. Then we have our homegrown migration file runner that will compute a hash of the migrations, make a database template_a5757f7e, and run the hundreds of migrations on it, whenever we add a new SQL migration (todo: make one template build on the previous). Then we use the BACKUP command to dump the db to disk (within the docker image) Finally, each test function is able to make a new database and restore that backup from file in less than a second. Populate with some relevant test data, run code, inspect results, drop database. So our test suite uses hundreds of fresh databases and it still runs in a reasonable time. (And..our test suite is written in Go, with a lot of embedded SQL strings, even if a lot of our business logic is in SQL)