MySQL vs csv files

antiseptic

antiseptic

Is there really any advantage to going through the trouble of setting of a MySQL database? What can I do with it that I can't do working with python and csv files?

Obviously, the big plus to csv files is simplicity. I don't really believe things should be any more complicated than necessary and it seems MySQL is a waste of time and effort. But I'm just throwing this question out there to see if someone can justify the learning curve.
 
Depends: Do you actually need any features of a DBMS (mysql), or do you just need to access a persistent but mostly static "list" (csv)? Ie. do you need the CRUD-features and/or transactional support, or just to read in mostly the same data? Though, if I really needed a DBMS, I'd go for Postgres.

A middle ground: If the data is not that important and mostly fits into memory, you could even serialize/deserialize yourself. Seems some people use Pickle for this. Though, beware that you may need to refactor existing data if you change how you access data in code later. Benefits to this is ability to rapidly prototype while not spending time on various data formats at an early stage.
 
i don't see the point in using a relational database for timeseries, i am never going to do an SQL join on these series.
i'm using arctic https://github.com/manahl/arctic as a timeseries store and am very impressed (speed and speaking pandas DataFrames natively), also doing csv backups though :)
 
I guess it depends of what are needs and what kind of data manipulation you need....For example if you want to perform some aggregations over a period of time...you need a database...no matter if it a RDBMS or NoSQL....
 
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