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This will all be down to the implementation of DataFrame no?

In other words if you put q ontop of a R DataFrame would you expect the same performance? Or if you ran R ontop of K.

I'm not sure if I understand your question correctly. kx provides shared libraries to make R and q talk to each other. The specific approach I followed used a shared library that brings R into the kdb+ memory space, meaning all the R statistical routines and graphing capabilities can be invoked directly from kdb+. Using this method means data is not passed between remote processes.

Ah I assumed you were loading a vanilla DataFrame from the column store. My bad :-)

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