Disclaimer: I work at Endeca, which just launched Latitdue, a mostly in-memory OLAP product. I work in the performance and scale group, and I've been experimen

Disclaimer: I work at Endeca, which just launched Latitdue, a mostly in-memory OLAP product. I work in the performance and scale group, and I've been experimenting with the speed of these things lately. As an experiment, I wrote a simple, stand alone program that takes a compressed database column and a list of which rows you care about, and does a group by with count. (We're a column store, so every column is stored separately.) For 1 billion records, it took about 250 ms. This is on a 4-socket Nehalem, so I had 32 cores and used 32 threads. If they're using Nehalems as well, and have 1 socket per box, they're using 320 cores. So they're about a factor of 40 slower than my simple experiment. To be sure, theirs was a general system that presumably runs on their actual data, whereas mine was just an experiment. Still, it seems quite possible to get the same result with significantly less hardware.