One project I'm working on these days is a large test suite for a Django project, in particular, trying to make it go faster. In one subset of 16 tests, total execution time is about 250 seconds! The tests clearly spend a lot of time in the database: 50% of the time is creating the test db, and another 30% is installing test fixtures.
A classic first step is to run the tests from an in-memory SQLite database. In this case, it's a Postgres database using GIS features, so changing engines isn't a simple settings change. Postgres doesn't have an in-memory feature, but I thought, why not force the database into memory without Postgres knowing, simply by creating the database in a ramdisk?
On Linux, this is a simple matter of creating the database in /dev/shm instead of a real disk-backed filesystem. And good thing it was simple, too, because it didn't help at all: the test times were completely indistinguishable between the two filesystems.
Which in retrospect makes perfect sense. Disk filesystems employ aggressive caching to keep data in memory in the first place, so it was unlikely that my simple trick was going to change things significantly. The test database is small enough to fit into RAM anyway, and for the tests, Postgres was already set to disable fsync.
The remaining mystery: why is SQLite in-memory faster than other databases on disk? If it is about the memory, then it should be possible to make other databases faster by forcing them into memory. And if isn't about the memory, then it's just that SQLite is faster no matter what (because it's in-process, for example) and using a disk-based SQLite should be faster than your real database also.