From your experience, how do SQL and python compare? I am obviously talking about data processing, data analytics, reporting but also perhaps wider data tasks such as automation, statistics, ETL, etc.
I could be looking to hear experiences on everything and hopefully particularly on speed, capabilities (what one can do that the other cannot), easiness of development of the code, integration with other systems, etc.
And after all, would you recommend to load data (EG from Excel or CSV files or connectors from other systems such as SAP) into a SQL on premises server or use Python? And which would be the critical parameters for your decision?
When you are working with a database as in SELECT, UPDATE, INSERT or DELETE you should always use SQL. SQL is the basic, it's easier to understand and more people are familier with it. If you load data on a regual basis you should use SQL.
For ad-hoc answering questions with data-analytics you should use python. With python it is much easier to create grafics, statistics etc.
Having said this, you should always make your own decision. It's more important that the job is done then how it's done. As a programmer you are growing each time and the quality of your code is improving each task.
I would say: SQL is more back-end, Python front-end. You can connect Python to SQL server and use the excute method to get the data, but in the end you will be executing a query on the database to get the data. So make it as performant as possible.