T Sql Indexing Inequality

Understanding `Inequality Testing in T-SQL`: Exploring `AND NOT`, `!=`, and `<>`

Inequality testing is an essential aspect of querying databases, and T-SQL offers several ways to achieve this. If you’ve found yourself pondering whether to use AND NOT (t.id = @id), AND t.id != @id, or AND t.id <> @id, you’re not alone. In this blog post, we’ll delve into these different approaches, discuss their performance implications, and help clarify the best practices for equality testing in T-SQL.

The Inequality Options in T-SQL

When constructing queries in T-SQL, you might encounter three common expressions of inequality:

Using AND NOT:
```
AND NOT (t.id = @id)
```
Using !=:
```
AND t.id != @id
```
Using <>:
```
AND t.id <> @id
```

At first glance, these expressions may appear interchangeable, but let’s break down how they compare and discuss any performance differences.

Execution Plans

When you analyze the execution plans for these expressions, you’ll find that they essentially yield the same outcome. For instance, consider the following SQL statements:

DECLARE @id VARCHAR(40)
SELECT @id = '172-32-1176'

SELECT * FROM authors
WHERE au_id <> @id

SELECT * FROM authors
WHERE au_id != @id

SELECT * FROM authors
WHERE NOT (au_id = @id)

In each of these cases, the execution plan produced will be identical. This means that regardless of the syntax chosen, the performance will be quite similar.

Indexing Considerations

While the result sets and execution plans remain consistent across these expressions, the potential impact on indexing is crucial to consider. Using both != and <> has the potential to hinder index use:

Index Usage: Utilizing != or <> can indeed disrupt any chances for effective index utilization. The SQL Server engine may face difficulties in optimizing the query performance when these operators are involved.
Using AND NOT: Similar to != and <>, the AND NOT clause also suffers from this limitation since the underlying comparison (t.id = @id) still results in a non-indexable condition.

Selectivity of the Index

It is important to note that the effectiveness of any index will also depend on its selectivity. Selectivity refers to how unique the indexed values are in a column:

High Selectivity: If the values in the index column are mostly unique, using <> or != may still yield performant queries.
Low Selectivity: Conversely, if the values are not distinct, the choice of operator becomes less relevant, as the engine will likely scan more of the table regardless.

Best Practices

After considering the mechanics of these inequality operators, here are a few best practices:

Stick with <>: Many T-SQL developers prefer using <> for clarity and standard adherence, making it immediately recognizable as an inequality operator.
Avoid !=: While != is also a valid operator, <> is the ANSI SQL standard and is typically favored for cross-database compatibility.
Use AND NOT Sparingly: Employ AND NOT when the logic requires it, but be mindful of its potential impact on the index, just like the other operators.