Almost all the Answers and Comments have been heavy on the Pros and light on the Cons. Here's a recap of all Pros and Cons so far plus some crucial Cons (in #2 below) I've only seen mentioned once or not at all.
- PROS:
1.1. More ISO compliant (ISO 8601) (although I don’t know how this comes into play in practice).
1.2. More range (1/1/0001 to 12/31/9999 vs. 1/1/1753-12/31/9999) (although the extra range, all prior to year 1753, will likely not be used except for ex., in historical, astronomical, geologic, etc. apps).
1.3. Exactly matches the range of .NET’s DateTime
Type’s range (although both convert back and forth with no special coding if values are within the target type’s range and precision except for Con # 2.1 below else error / rounding will occur).
1.4. More precision (100 nanosecond aka 0.000,000,1 sec. vs. 3.33 millisecond aka 0.003,33 sec.) (although the extra precision will likely not be used except for ex., in engineering / scientific apps).
1.5. When configured for similar (as in 1 millisec not "same" (as in 3.33 millisec) as Iman Abidi has claimed) precision as DateTime
, uses less space (7 vs. 8 bytes), but then of course, you’d be losing the precision benefit which is likely one of the two (the other being range) most touted albeit likely unneeded benefits).
- CONS:
2.1. When passing a Parameter to a .NET SqlCommand
, you must specify System.Data.SqlDbType.DateTime2
if you may be passing a value outside the SQL Server DateTime
’s range and/or precision, because it defaults to System.Data.SqlDbType.DateTime
.
2.2. Cannot be implicitly / easily converted to a floating-point numeric (# of days since min date-time) value to do the following to / with it in SQL Server expressions using numeric values and operators:
2.2.1. add or subtract # of days or partial days. Note: Using DateAdd
Function as a workaround is not trivial when you're needing to consider multiple if not all parts of the date-time.
2.2.2. take the difference between two date-times for purposes of “age” calculation. Note: You cannot simply use SQL Server’s DateDiff
Function instead, because it does not compute age
as most people would expect in that if the two date-times happens to cross a calendar / clock date-time boundary of the units specified if even for a tiny fraction of that unit, it’ll return the difference as 1 of that unit vs. 0. For example, the DateDiff
in Day
’s of two date-times only 1 millisecond apart will return 1 vs. 0 (days) if those date-times are on different calendar days (i.e. “1999-12-31 23:59:59.9999999” and “2000-01-01 00:00:00.0000000”). The same 1 millisecond difference date-times if moved so that they don’t cross a calendar day, will return a “DateDiff” in Day
’s of 0 (days).
2.2.3. take the Avg
of date-times (in an Aggregate Query) by simply converting to “Float” first and then back again to DateTime
.
NOTE: To convert DateTime2
to a numeric, you have to do something like the following formula which still assumes your values are not less than the year 1970 (which means you’re losing all of the extra range plus another 217 years. Note: You may not be able to simply adjust the formula to allow for extra range because you may run into numeric overflow issues.
25567 + (DATEDIFF(SECOND, {d '1970-01-01'}, @Time) + DATEPART(nanosecond, @Time) / 1.0E + 9) / 86400.0
– Source: “ https://siderite.dev/blog/how-to-translate-t-sql-datetime2-to.html “
Of course, you could also Cast
to DateTime
first (and if necessary back again to DateTime2
), but you'd lose the precision and range (all prior to year 1753) benefits of DateTime2
vs. DateTime
which are prolly the 2 biggest and also at the same time prolly the 2 least likely needed which begs the question why use it when you lose the implicit / easy conversions to floating-point numeric (# of days) for addition / subtraction / "age" (vs. DateDiff
) / Avg
calcs benefit which is a big one in my experience.
Btw, the Avg
of date-times is (or at least should be) an important use case. a) Besides use in getting average duration when date-times (since a common base date-time) are used to represent duration (a common practice), b) it’s also useful to get a dashboard-type statistic on what the average date-time is in the date-time column of a range / group of Rows. c) A standard (or at least should be standard) ad-hoc Query to monitor / troubleshoot values in a Column that may not be valid ever / any longer and / or may need to be deprecated is to list for each value the occurrence count and (if available) the Min
, Avg
and Max
date-time stamps associated with that value.