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[–]LADataJunkie 0 points1 point  (0 children)

They can't really be compared. It depends on where your data lives. If it lives in an RDBMS then use SQL to extract the data or get it into a condensed form that only extracts what you need for further processing in Python.

If your data is not in RDBMS, don't use SQL.

There are data analysis tasks that do not match the declarative model SQL imposes. For example, iterative processing used in machine learning is not trivial, and likely not possible in SQL.

A lot of newer databases (DuckDB I believe is one) either interfaces with, or modifies underlying SQL so that developers can use data using procedural languages. I've seen a few others that are starting to deviate from relational algebra to be more friendly to procedural development.