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Book: PostgreSQL 9.0 High Performance
Very sensible, worth reading, even if you do not have PostgreSQL, because, firstly, there is a lot of useful information about the iron part, and secondly, many things make sense for other DBMS, taking into account their specifics , certainly.
By itself, the Python code, kmk, makes sense to optimize after the libraries for bottlenecks are correctly selected, that is, if there is a large network load, then twisted / tornado, if there are a lot of calculations - numpy / scipy, and so on.
And after the optimal data processing algorithms are selected.
The architecture is optimized for high loads, and the code and base are a secondary matter. Often even the opposite rule applies - with identical functionality of two architectures, one works slower at a small load, but faster at a large one, and, most importantly, holds a large load.
In general, I would advise you to read highscalability.com/
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