In Data Science, many seem to be using pandas dataframes as the datastore. What are the features of pandas that make it a superior datastore compared to regular relational databases like MySQL, which are used to store data in many other fields of programming?While pandas does provide some useful functions for data exploration, you can't use SQL and you lose features like query optimization or access restriction.
Advantages of pandas dataframe to regular relational database
pandas;databases
I think the premise of your question has a problem. Pandas is not a datastore in the way an RDBMS is. Pandas is a Python library for manipulating data that will fit in memory. Disadvantages:Pandas does not persist data. It even has a (slow) function called TO_SQL that will persist your pandas data frame to an RDBMS table.Pandas will only handle results that fit in memory, which is easy to fill. You can either use dask to work around that, or you can work on the data in the RDBMS (which uses all sorts of tricks like temp space) to operate on data that exceeds RAM. 