How to Use Like in SQL: Pattern Matching for Precise Data Queries

Searching databases without exact matches felt impossible until I discovered pattern matching. The solution is simpler than most tutorials make it seem, and it works across MySQL, PostgreSQL, and SQL Server.

Wildcards like % and _ transform basic queries into powerful filters. I’ve used this to find customer names starting with “J” or product codes ending with “2024” in under a minute of writing the first query.

You’ll spot partial matches, handle typos gracefully, and pull data you didn’t even know was buried in your tables. No special tools, just the right syntax.

The trick is knowing where to place those wildcards. Get it wrong and you’ll pull zero results—or worse, too many. Here’s the foolproof approach.

What Youll Need

Instructions

Here’s the procedure I follow to harness pattern matching for precise data filtering.

The LIKE operator relies on two wildcard characters: the percent sign % and the underscore . The percent sign matches any sequence of characters, including none. For example, ‘a%’ matches any string starting with “a”, like “apple” or “advantage”.

The underscore matches exactly one character. So ‘at’ matches “cat”, “bat”, or “hat”, but not “chat”. I always test these patterns in a query tool first to see how they behave with my actual data.

Start with simple patterns to get comfortable. To find all customers whose names start with “J”, use WHERE name LIKE ‘J% ‘. This returns “James”, “John”, and “Jenny”, but not “Mary Jane” (unless the name field is formatted that way).

For names ending with a specific pattern, reverse the wildcard: ‘%son’ matches “Johnson”, “Jackson”, or “Wilson”. I’ve found that combining both like ‘%son%’ catches any occurrence, but be aware this can slow down queries on large tables.

The underscore is powerful for fixed-length patterns. To find all 4-letter product codes where the first two letters are “AB”, use WHERE code LIKE ‘AB‘. This matches “AB12” or “ABCD”, but not “AB1” or “AB123”.

For phone numbers stored as strings, LIKE ‘––__’ ensures the format is exactly three digits, hyphen, three digits, hyphen, four digits. This prevents partial matches that % would otherwise allow.

If you need to search for literal wildcard characters, use the ESCAPE clause. For example, to find strings containing %, write WHERE column LIKE ‘%\%%’ ESCAPE ‘\’. The backslash tells SQL to treat the following % as a literal character.

This is particularly useful when working with data that includes percentages or underscores as part of the content. Without the escape, SQL interprets these as wildcards, which can lead to unexpected results or errors.

Real-world queries often need more precision. Combine LIKE with other operators using AND or OR. For instance, WHERE name LIKE ‘J%’ AND age > 30 finds all “J” names over 30.

For multiple patterns, use OR: WHERE name LIKE ‘J%’ OR name LIKE ‘M%’ returns names starting with either letter. I always parenthesize complex conditions to ensure the logic evaluates as intended.

Tips & Tricks for Perfect Data Pattern Matching

These techniques have saved me countless hours when working with large datasets in SQL.

The Wildcard Breakdown: In Step 1, understanding that % matches any sequence (including none) while matches exactly one character is fundamental. I learned this the hard way when my early queries returned unexpected results because I misapplied the underscore for variable-length patterns.