Category: Data Types

Greg Low has some thoughts around data types and sizes:

I was recently at a site where they were changing all their bigint columns to uniqueidentifier columns (ie: GUID columns) because they were worried about running out of bigint values. In a word, that’s ridiculous. While it’s easy to say “64 bit integer”, I can assure you that understanding the size of one is out of our abilities. In 1992, I saw an article that said if you cleared the register of a 64 bit computer and put it in a loop just incrementing it (adding one), on the fastest machine available that day, you’d hit the top value in 350 years. Now machines are much faster now than back then, but that’s a crazy big number.

If you’re at risk of running out of bigints, you have a lot of data—that’s more than 18 quintillion rows that you can hold, and if my quick math is up to snuff, would be roughly 127 thousand petabytes of data just to store the IDs.

Randolph West unravels a mystery around byte lengths:

Quite a lot to take in. Let’s break this down.

DATETIME2 is a data type that was introduced in SQL Server 2008. It uses up to 8 bytes to store a date and time: 3 bytes for the date component, and up to 5 bytes for the time component.

The point here is that it uses 8 bytes in total. That’s it. No more.

Jemma noted that when converting the DATETIME2 data type to BINARY, it suddenly became longer by exactly one byte, which seems strange.

Read on for the solution.

Louis Davidson walks through some of the properties of rowversion data types:

For years, I had thought (and was probably taught in SQL.AlongTimeAgoInAPlaceFarFarAway) that the timestamp column (well before rowversion was a thing,) was not guaranteed to be an ever increasing value. But this is not the case.

In BOL (https://docs.microsoft.com/en-us/sql/t-sql/data-types/rowversion-transact-sql)  it states:

“The rowversion data type is just an incrementing number…”

This makes it useful for determining rows that have changed, because it it automatic and the user cannot override the value in the column. However, there is a major concern when you use rowversions, and that is what happens when you change the structure of the table, and expect the consumer to see that change. The problem is that when you change the structure of the table, the rowversion will not be set (except when adding a new rowversion column.)

I’m not much of a fan of rowversion and tend not to use it, but my biases don’t have to be yours.

Raul Gonzalez shows how to get one of the benefits of older, deprecated data types using (MAX) data types:

We can see that our table is managed by two different allocation units, IN_ROW_DATA and LOB_DATA, which means that all data within columns of the data types above, will end up in different pages by default, regardless of the size of the data.

This is the default behaviour for old LOB types, to be stored separately, but new LOB types (MAX) by default will try to get them In-Row if they are small enough to fit.

Having some of those documents In-Row will result in a serious increase in the number of pages to scan, therefore affecting performance.

Note that for the table scan we have used only the IN_ROW_DATA pages, making it much lighter than if we have to scan the sum of all pages.

This might be helpful for some situations, like where you rarely need to get to the LOB data.

Erik Darling warns against using SQL_VARIANT data types:

I half-stumbled on the weirdness around SQL_VARIANT a while back while writing another post about implicit conversion. What I didn’t get into at the time is that it can give you incorrect results.

When I see people using SQL_VARIANT, it’s often in dynamic SQL, when they don’t know what someone will pass in, or what they’ll compare it to. One issue with that is you’ll have to enclose most things in single quotes, in case a string or date is passed in. Ever try to hand SQL those without quotes? Bad news bears. You don’t get very far.

Read on for the demo.  I have never used SQL_VARIANT in any project.  I’ve done a lot of crazy things with SQL Server (some of them intentionally) but never this.