> does it have a wicked lower TCO because you literally have insanely less lines of liability in your code, libraries, dependencies, etc?
Yes. q (a language and distribution of k4) has a built-in webserver with websockets, messaging, all types can be serialised over IPC (except pointers to C code) and most data structures have an efficient on-disk representation.
You might've recalled a few days ago someone announced a specialised database for doing "have-i-been-pwned" lookups in 49µsec. I wrote[1] one line of q that is about 10x faster:
It's just a single operation, and it's built-in, so maybe you think Python could just have mmap-efficient variables and a bin operator and you'd be there, but those things don't exist in Python. If I had the same problem as the author, it certainly wouldn't materialise as "custom database" of any kind, because I'd already be done.
In fact, one of the biggest challenges with "big data" is choosing an efficient representation. The author spent a lot of time on this, but my language just had one built-in. How much time? What's the target? I mean, if I've already paid for q it's clearly a no-brainer, but q isn't free either (even if you get it for no cost: you still need to learn it!)
> Is that the reason finance uses it, they maybe empirically know what the rest of us don't seem to grasp? Or just because it's so domain specific? Or... something else entirely?
Back in the day, k was the only thing you could put tick data into. Now there's lots of systems, and computers are a lot faster, so quants can use Python. Their code doesn't need to be "fast", but "fast enough".
Yes. q (a language and distribution of k4) has a built-in webserver with websockets, messaging, all types can be serialised over IPC (except pointers to C code) and most data structures have an efficient on-disk representation.
You might've recalled a few days ago someone announced a specialised database for doing "have-i-been-pwned" lookups in 49µsec. I wrote[1] one line of q that is about 10x faster:
[1]: https://news.ycombinator.com/item?id=22467866
It's just a single operation, and it's built-in, so maybe you think Python could just have mmap-efficient variables and a bin operator and you'd be there, but those things don't exist in Python. If I had the same problem as the author, it certainly wouldn't materialise as "custom database" of any kind, because I'd already be done.
In fact, one of the biggest challenges with "big data" is choosing an efficient representation. The author spent a lot of time on this, but my language just had one built-in. How much time? What's the target? I mean, if I've already paid for q it's clearly a no-brainer, but q isn't free either (even if you get it for no cost: you still need to learn it!)
> Is that the reason finance uses it, they maybe empirically know what the rest of us don't seem to grasp? Or just because it's so domain specific? Or... something else entirely?
Back in the day, k was the only thing you could put tick data into. Now there's lots of systems, and computers are a lot faster, so quants can use Python. Their code doesn't need to be "fast", but "fast enough".
My code still needs to be fast though.