This is a general question without code samples or specifics on the structures being implemented. I'd appreciate any applicable feedback on the overall approach. I'm working on implementing a partitioned table/index structure for a large denormalized table. I used the Kimberly Tripp article and 2008 Books Online as a guide. I defined the partitons based on the most commonly used date range selections (Today, Last 7, Last 30, Last 60), end expected to see better results with the partition approach particularly on the Last 30 and Last 60 periods, since the query had to search back through a significant date range but much less data logically (because of the partitions). There is a year and half worth of data in the table. The table, clustered indices, and nonclustered indices all utilize the partition structure. My overall finding is that there doesn't seem to be much improvement between our normal clustered index use on the date column and the partitioned table using the same date column. I'm wondering if the fact that the underlying disk structure is the same (single disk being used in both the primary filegroup appraoch and the partition scheme approach), I'm not going to get much improvement over the simpler clustered index approach.