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Intel IOMeter Database Pattern

You’ll now see the drives perform under a load typical of database servers. This IOMeter pattern is sending requests to read and write 8KB data blocks. Throughout the test, the outstanding request queue is getting deeper and the percentage of reads to writes is changing, too.

For each array type there are three diagrams that show the dependence of performance on the percentage of write requests at three different loads (1, 16 and 256 outstanding requests).

The Hitachi drive gains the lead in a RAID0 array under low load, but it is outperformed by the Western Digital HDDs as the percentage of writes grows up. In the Random Write mode (i.e. at 100% writes), the Maxtor suddenly leaps to first place, although it shares last places with the Seagate drive at lower percentages of writes.

At higher load the WD drives are ahead of the Hitachi from the very start. Especially good is the WD4000KS model which is in the lead most of the time. It only proves to be slower than the previous generation of WD drives at some percentages of writes.

It is the Seagate HDD that occupies last place, just like in the previous case.

The WD4000KS is just immodestly superior to the other HDDs at this load. I guess its success is indicative of its NCQ support, but the WD website keeps silent on that subject.

Note also the small success of the Seagate drive, but it is indeed small in comparison with the WD4000KS.

Let’s now see if anything’s different when the HDDs work in RAID5.

Here is a good illustration of how the controller’s algorithms may affect performance of a RAID array. Note the jagged shape of the graphs – this is the consequence of a conflict between the controller’s algorithms and the HDDs’ deferred writing.

Note also that the Hitachi is not as good as in RAID0, but the drives from WD are on top again, the WD4000KS still being the best of them.

 
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