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Category: Data Types

Choosing between String Data Types in SQL

Greg Larsen compares CHAR, VARCHAR, and VARCHAR(MAX):

In every database, there are different kinds of data that need to be stored. Some data is strictly numeric, while other data consists of only letters or a combination of letters, numbers, and even special symbols. Whether it is just stored in memory or on disk, each piece of data requires a data type. Picking the correct data type depends on the characteristics of the data being stored. This article explains the differences between CHARVARCHAR, and VARCHAR(MAX).

Click through for Greg’s explanation. My official rule of thumb is as follows:

  • If you have a fixed-length code which you display to customers, use NCHAR.
  • If you have a fixed-length code which you only use internally and you know that the code will never include characters outside of your SQL Server installation’s code page and you know that the code page will never change…probably still use NCHAR, though if you twist my arm enough I’d say fine, CHAR.
  • Otherwise, use NVARCHAR.

Three decades ago, the choice was a lot trickier given performance differences between the two. Today? Unless you’re hunting for microseconds I don’t think you’ll see a practical difference. And if you are hunting for microseconds, you probably want more than rules of thumb.

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Swap an Identity Column with a Sequence

Greg Larsen looks at sequences:

Microsoft introduced the sequence number objects starting with SQL Server 2012. A sequence object generates sequence numbers based on starting and increment values, similar to an identity column, but it has additional features. Over time, you might find that the additional benefits of a sequence number have you wanting to replace an identity column with a sequence number. This article demonstrates two options for replacing an identity column with a sequence number.

When it came out, I thought I was going to use sequences a quite often. In practice, I’ve used it a few times, but IDENTITY is so much easier to type and I’ve rarely needed sequence generators. That said, the times I have needed them, I definitely appreciate their existence.

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Wildcards and Data Type Precedence

Daniel Hutmacher has fun with implicit conversion:

Implicit conversions in SQL Server follow a specific, predictable order, called data type precedence. This means that if you compare or add/concatenate two values, a and b, with different data types, you can predict which one will be implicitly converted to the data type of the other one in order to be able to complete the operation.

I stumbled on an interesting exception to this rule the other day.

Click through for an example of date searching with LIKE.

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On Avoiding NULL

Aaron Bertrand defends NULL:

A long time ago, I answered a question about NULL on Stack Exchange entitled, “Why shouldn’t we allow NULLs?” I have my share of pet peeves and passions, and the fear of NULLs is pretty high up on my list. A colleague recently said to me, after expressing a preference to force an empty string instead of allowing NULL:

“I don’t like dealing with nulls in code.”

I’m sorry, but that’s not a good reason. How the presentation layer deals with empty strings or NULLs shouldn’t be the driver for your table design and data model. And if you’re allowing a “lack of value” in some column, does it matter to you from a logical standpoint whether the “lack of value” is represented by a zero-length string or a NULL? Or worse, a token value like 0 or -1 for integers, or 1900-01-01 for dates?

Definitely read what Aaron has to say. I disagree with the tenor of his point enough that, now that I’m actually blogging again, I’ll have a post up tomorrow laying out the core of my disagreement. Stay tuned!

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Data Type Casing in SQL Server

Aaron Bertrand finds a case where casing matters:

We all have coding conventions that we have learned and adopted over the years and, trust me, we can be stubborn about them once they’re part of our muscle memory. For a long time, I would always uppercase data type names, like INTVARCHAR, and DATETIME. Then I came across a scenario where this wasn’t possible anymore: a case-sensitive instance. In a recent post, Solomon Rutzky suggested:

As long as you are working with SQL Server 2008 or newer, all data type names, including sysname, are always case-insensitive, regardless of instance-level or database-level collations.

I have a counter-example that has led me to be much more careful about always matching the case found in sys.types.

Click through for that scenario.

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Implicit Conversions and SARGability

Erik Darling bears bad news:

Data types are one of those core things you need to get right. Whether it’s matching types between join columns, or between parameters and predicates, not doing so can really squash application performance in quite similar ways to writing non-SARGable predicates.

That’s because — wait for it — a lot of the stuff we’ve talked about over the last week that can happen with poorly written predicates can happen with poorly matched data types, too.

Click through for an example. If this keeps up, we may never save Sarge.

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Working with Complex Return Types in Power Query

Gerhard Brueckl works with some complex data:

When working with Power Query, you have probably already realized that every expression you write returns a value of a specific type. Usually this will be a primitive type like text, number, or date. (A full list of types available in Power Query can be found here: https://docs.microsoft.com/en-us/powerquery-m/m-spec-types). If for some reason the type of an expression cannot be defined, the special type *any* will be used. For sure you already encountered this when using Table.AddColumn which, by default, results in the new column being of type *any*.

Read on to learn more, including what you can do if you’re creating Power Query functions.

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