The missing link here, and the reason Python gets more love from the data community, is that Python scales down to the smaller data sets as well as it handles big ones. (Not sure if you ment it couldn't, but the distinction you make implies that.)
EDIT: or did you mean Disco offers distributed sparse CSC operations?
For example, instead of computing an exact SVD, you will use something like Hebbian algorithm to compute the SVD in a streaming manner (that's what Mahaout implements for example).
Both R and Ruby have had issues with large data sets which have been addressed to some degree in more different distributions and more recent releases. Python is ready out of the box for large data sets. So what I meant to communicate is that if you know that you are going to be dealing with a large data set, you might as well go straight to python.