R Benchmarks on a big data logistic regression

We did some benchmarks of a logistic regression for a customer with a million rows data set. I know it is not a "BIG DATA" problem for many people, but slightly big sounds stupid. We ran the benchmarks on the following setup:


CPU: Intel Xeon X5570 2.93GHz
CPU cores: 8
RAM: 23GB
Network: 10-gigabit ethernet


We used standard open source R 2.14 with glm, Revolution R with glm and Revolution R with "rxlogit". The results were as follows:


R 2.14 with glm: 56 sec
RevoR with glm: 54 sec
RevoR with rxlogit: 7 sec


I can not really provide more information than that, but I think the results are compelling that in some cases Revolution R with rxlogit is far superior in terms of speed for problems of a certain size problems.