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q/kdb+ is used in finance (banking + funds) for heavy numerical computation every day. high-volume realtime data straight from markets, and petabyte/trillion-row historical DBs. it runs on CPU but computation easily parallelizes over cores/clusters.

regarding use cases, see https://kx.com/resources/use-cases/

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Thanks, that gives me better feel for it. Mostly analytics, good with large datasets, but probably not great for things where you get a big gain from GPU?

what tasks are you thinking? i'm not a gpu expert

q is good with bulk operations on compact arrays; these are cache-friendly and the interpreter can utilize cache-level parallelism. and with q it's convenient to go from idea -> MVP in short time. it's a high-level language with functional features so expressing algos and complex logic is natural.

but it's interpreted and optimized for array ops. so really latency-critical (e.g. high-freq trading) or highly scalar logic will be done with C++. the trade-off is convenience of development.

Hedge funds use ML

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