The data.table R package is really good at sorting. Below is a comparison of it versus dplyr for a range of problem sizes.
The graph is using a log-log scale (so things are very compressed). But data.table is routinely 7 times faster than dplyr. The ratio of run times is shown below.
Notice on the above semi-log plot the run time ratio is growing roughly linearly. This makes sense: data.table uses a radix sort which has the potential to perform in near linear time (faster than the n log(n) lower bound known comparison sorting) for a range of problems (also we are only showing example sorting times, not worst-case sorting times).
In fact, if we divide the y in the above graph by log(rows) we get something approaching a constant.
The above is consistent with data.table not only being faster than dplyr, but also having a fundamentally different asymptotic running time.
Performance like the above is one of the reasons you should strongly consider data.table for your R projects.
All details of the timings can be found here.
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