Understanding DATEADD And DATEDIFF

Matan Yungman and Guy Glantser take a hack at DATEDIFF versus DATEADD for date calculations.  First up is Matan:

Pretty simple right?

Well, it is, and since this problem is pretty common, I used this solution in many performance tuning sessions I performed over the years.

There’s a slight problem though: This solution isn’t 100% accurate.

When carefully looking at the results, I find out that for the first query, I get 5859 rows, and for the second query, I get 5988 rows. Where does this difference come from?

Then, Guy gives his take on the problem:

I tested both queries on a sample table, which has millions of rows, and only around 500 rows in the last 90 days. The first query produced a table scan, while the second query produced an index seek. Of course, the execution time of the second query was much lower than the first query.

Both queries were supposed to return the orders in the last 90 days, but the first query returned 523 rows, and the second query returned 497 rows. So what’s going on?

The answer has to do with the way DATEDIFF works. This function returns the number of date parts (days, years, seconds, etc.) between two date & time values. It does that by first rounding down each one of the date & time values to the nearest date part value, and then counting the number of date parts between them.

They both start from the same base problem, but end up with slightly different formulations of a solution.

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