HDF5 and BioSQL solutions
Just to conclude, @user172818 and @AlexReynolds are collectively saying either learn SQL or stick with CSV. 



Update,
I can provide an answer. It's HDF5 with pandas dataframes (Python).

Simply

df.to_hdf('path/file.h5', 'key', format='table')


This isn't SQL but it works:

What it gives,


it's fast, that's it's purpose (not my main reason though)
it perfectly preserves all pandas dataframe information, this is  important
The 'key' ( object) allows you to store multiple dataframes into the same file, you just provide different key names


The last point is very useful, because you can pull out a dataframe of choice and the SQL commands are mimicked within pandas

I ran into trouble using CSV to store/recover complex pandas dataframe formats. 

So it's good enough and much faster than SQL. I could have problems with format changes in time (unlike SQL), but for the here and now it works well. 



Just to add a caveat, for dictionaries the json dump works well, but it is just shunting dictionaries around, so isn't relevant.