"Moreover, support for dplyr and data.table are on the way. "

Well, I can't really use it in my day to day work, since that almost always involves cleaning and munging via one of those two packages. And it's not like ggplot2 is where my R code is most delayed, usually I'm working on aggregate data or perhaps a very much smaller analytical dataset which requires much less speed for plotting. My hang-ups are in initial munging phases where the data is still very large, which often calls for data.table over dplyr due to the latter's much slower performance.