I process a lot of text/data that I exchange between Python, R, and sometimes Matlab.
My go-to is the flat text file, but also use SQLite occasionally to store the data and access from each program (not Matlab yet though). I don't use GROUPBY, AVG, etc. in SQL as much as I do these operations in R, so I don't necessarily require the database operations.
For such applications that requires exchanging data among programs to make use of available libraries in each language, is there a good rule of thumb on which data exchange format/method to use (even XML or NetCDF or HDF5)?
I know between Python -> R there is rpy or rpy2 but I was wondering about this question in a more general sense - I use many computers which all don't have rpy2 and also use a few other pieces of scientific analysis software that require access to the data at various times (the stages of processing and analysis are also separated).
If all the languages support SQLite - use it. The power of SQL might not be useful to you right now, but it probably will be at some point, and it saves you having to rewrite things later when you decide you want to be able to query your data in more complicated ways.
SQLite will also probably be substantially faster if you only want to access certain bits of data in your datastore - since doing that with a flat-text file is challenging without reading the whole file in (though it's not impossible).