Python DataScience Library vs SQL

I am working on a project where there is a necessity to store considerable data. I was wondering what is the difference between using SQL and the datascience library in python. I intend to use SQL from its python based libraries too or use a csv file to store info if I am going to use datascience. I am leaning very much towards datascience as I find the following advantages:

It is subjectively very easy to use for me. I make much less mistakes. With my limited knowledge in runtime, I think the datascience library will be more efficient. Most importantly, it has many inbuilt functions that could allow me to make easier functions. However, since so many people are using SQL, I was wondering if I am missing something major, particularly in scalability.

Some people online said that SQL allows us to store files on a database, but I do not see how that makes a difference. I can simply store the file in a folder on a system and save the link in the datascience table.