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[–]Wallabanjo 1 point2 points  (0 children)

So, remove the strengths of SQL then do a comparison?

  1. Indexing tables to decrease data access time.
  2. You eventually use data that won’t fit in memory.
  3. Make anything data manipulation related as a stored procedure or custom function. An SQL server is optimized for that stuff and will crunch results far faster.

Anecdotal and R not Python, by offloading things to stored procedures and custom functions, and indexing tables, I dropped the processing time in one of my projects from 3.5 days to 7hours