SQL `LIKE` vs `=`: When Does `LIKE` Outperform `=`?

SQL 'LIKE' vs '=' Performance: A Comprehensive Analysis

Introduction

The choice between using the 'LIKE' and '=' operators in SQL queries can significantly impact performance. In general, '=' is considered faster than 'LIKE' when using wildcards. However, there are exceptions to this rule that can reverse the performance implications.

Specific Case Analysis

In the given context, where a column contains a limited number of different fixed identifiers and the goal is to select rows matching a specific one, the 'LIKE' operator may actually provide an advantage over '='.

• 'LIKE' Operator:

  • Only needs to test the first few characters to find a match.
  • In the example provided (value like 'abc%'), it compares only the first three characters.

• '=' Operator:

  • Must compare the entire string.
  • In the example provided (value = 'abcdefghijklmn'), it compares the entire 15-character string.

Based on this analysis, one would expect 'LIKE' to perform better in this specific situation, especially considering the smaller data set size.

Index Usage Considerations

In practice, the impact of index usage on performance must also be considered. According to the rules outlined in the cited resource:

• '=' is more likely to use an index seek, resulting in faster performance when the field is indexed.
• 'LIKE' with no wildcards (like a parameter with a potential '%') is about as likely to use the index as '='.
• 'LIKE' with a wildcard at the beginning is less likely to use the index, but may still perform an index scan.
• 'LIKE' with a string first and wildcards after may use an index seek to find starting characters and then perform an exact match scan.

In conclusion, while '=' is generally faster than 'LIKE' when using wildcards, there are specific circumstances where 'LIKE' may offer better performance, such as when querying a limited set of fixed identifiers with a wildcard at the beginning of the string. As always, testing in the specific context is crucial to determine the optimal approach for a given query.

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