In my experience, kdb+'s k and q (which is broadly speaking a legibility wrapper around k, which again broadly speaking is APL without unicode) are phenomenally fast for dense time series datasets. Though they can struggle (relatively, still pretty fast) with sparse data that's not really what they are built for. They were built for high-performance trading systems, and trading data is dense. If you like writing dens…
The biggest messes I have to clean up come less from "clever" code than they do from people who try to program in K as if it were some other language. For example, somebody fond of for loops might write the following to apply a function 'f' to pairings of values and their index in a list:
result:()
i:0
do[#v
r:r,,f[v[i];i]
i:i+1
]
Ugly, complicated, but "close at hand". There is of course a much nicer and more idiomatic way to do the same thing: result: f'[v;!#v]
Most of the time conciseness isn't the goal, but you get it as a side effect of writing good code and working "with the grain" of the language.