I use both. R is slow as a dog, Q/KDB+ is (almost) as quick as C. R is ugly, Q/K is beautiful and elegant. R has a wealth of open-source packages, Q not so much.

Best solution is to do most of your work in Q and call into R when you want to use a package. The R integration works well, see http://code.kx.com/wiki/Cookbook/IntegratingWithR.

The reality is that if you are using (and paying for) Q/K, you are likely doing so because you're dealing with billion+ point datasets. At least. R just melts and falls apart at that kind of size (without using native code, which isn't really R then is it?). So I often end up just translating R functions into K equivalent, and just using R for the nice-to-have features like latex/brew/ggplot/etc.