In fact, I'd say it's extremely common for database workloads to be compute bound on modern hardware.
For one, storage bandwidth has increased massively (my laptop's NVMe drives can do 2 x 3.2GB/s reads, you can get quite a few into even small servers). While memory latency and CPU throughput have not increased to the same degree.
To benefit from the increases in CPU throughput, one needs to take advantage of superscalar execution. Which isn't significantly possible with interpreted execution.
> SQLite3 compiles queries into bytecode, while PostgreSQL compiles them into AST-like tree structures
FWIW, expressions are compiled into bytecode in PostgreSQL as well. While there'd plenty benefit of doing that for query trees as well, there are not quite as much raw execution speed reason for it as there is for expressions (as the individual "steps" are much coarser, so the tree walk overhead is proportionally smaller).
For one, storage bandwidth has increased massively (my laptop's NVMe drives can do 2 x 3.2GB/s reads, you can get quite a few into even small servers). While memory latency and CPU throughput have not increased to the same degree.
To benefit from the increases in CPU throughput, one needs to take advantage of superscalar execution. Which isn't significantly possible with interpreted execution.
> SQLite3 compiles queries into bytecode, while PostgreSQL compiles them into AST-like tree structures
FWIW, expressions are compiled into bytecode in PostgreSQL as well. While there'd plenty benefit of doing that for query trees as well, there are not quite as much raw execution speed reason for it as there is for expressions (as the individual "steps" are much coarser, so the tree walk overhead is proportionally smaller).