Indeed, and if you have a community of people using them, you can be very productive.

But those languages are astonishingly intimidating for new programmers -- reading from right to left, with implicit variables, different usage of brackets, types that are hard to discern, overloading of every possible bit of punctuation, etc makes it more like translating Latin than writing code.

So while a line such as : .[`:/data/raw; (); :; 1001 1002 1003]

is very succinct, the skill and concentration necessary to write that line is not something that lends itself to widespread adoption.

I've been learning APL for a bit, and have tried q too, and I disagree with the idea you need more skill and concentration to write either. Personally, for problems that suit the domain, I've found it much easier than equivalents in other languages like numpy and pandas. Q-sql in particular seems extremely convenient to have built into a language, and probably requires less concentration to write than an equivalent using manual iteration/filtering.

Yes, sorry for not mentioning that. I'm aware of kdb+ in finance (never used it personally, but wish I could).