SQL LIKE Operator

In the world of SQL, the ability to perform pattern matching within textual data is a crucial skill for crafting precise and flexible queries. The SQL LIKE operator emerges as a powerful tool, enabling developers to filter and retrieve data based on specified patterns or partial strings. Join us on an in-depth exploration as we unravel the intricacies of the SQL LIKE operator, understanding its syntax, exploring use cases, and showcasing its pivotal role in crafting dynamic and efficient queries.

The Essence of SQL LIKE Operator

The SQL LIKE operator is employed to search for a specified pattern within a column or string. It allows developers to perform partial string matching, making it a versatile tool for retrieving data that conforms to specific criteria. The basic syntax of the SQL LIKE operator is as follows:

-- LIKE Syntax
SELECT column_name(s)
FROM table_name
WHERE column_name LIKE pattern;
  • column_name(s): The column or columns to be retrieved.
  • table_name: The table from which data is retrieved.
  • column_name LIKE pattern: The condition specifying the pattern to match. The pattern can include wildcards such as ‘%’ (matches any sequence of characters) or ‘_’ (matches any single character).

Basic Examples of SQL LIKE Operator

Retrieving Names Starting with “John”:

SELECT employee_name
FROM employees
WHERE employee_name LIKE 'John%';

In this example, the query retrieves the names of employees from the ’employees’ table where the name starts with “John.”

Finding Email Addresses in a Specific Domain:

SELECT email
FROM customers
WHERE email LIKE '%@example.com';

Here, the query retrieves email addresses from the ‘customers’ table that belong to the domain “@example.com.”

SQL LIKE with Wildcards

The power of the SQL LIKE operator lies in its ability to use wildcards for flexible pattern matching.

  • The ‘%’ wildcard: Represents any sequence of characters (including zero characters).
  • The ‘_’ wildcard: Represents any single character.

Matching Names Ending with “son”:

SELECT last_name
FROM customers
WHERE last_name LIKE '%son';

This query retrieves last names from the ‘customers’ table where the last name ends with “son.”

Finding Three-Letter Words:

FROM dictionary
WHERE word LIKE '___';

Here, the query retrieves words from the ‘dictionary’ table that consist of exactly three characters.

Use Cases for SQL LIKE Operator

  1. Textual Search:
  • Search for records containing specific words or phrases within textual data.
  1. Data Validation:
  • Validate data formats, such as email addresses or phone numbers.
  1. Dynamic Filtering:
  • Craft dynamic queries to filter records based on user input or changing criteria.
  1. Pattern Matching:
  • Conduct pattern matching to identify and retrieve data based on specified patterns.

Considerations and Best Practices

  1. Case Sensitivity:
  • The behavior of the LIKE operator might be case-sensitive or case-insensitive depending on the database system. Be aware of the case sensitivity and adjust the query accordingly.
  1. Indexing Impact:
  • Extensive use of leading wildcards, especially ‘%’, can impact query performance, as it might hinder the use of indexes. Consider alternatives or optimize the database schema for such scenarios.
  1. Escaping Special Characters:
  • If the pattern includes special characters like ‘%’ or ‘_’, and you want to search for these characters explicitly, use the ESCAPE clause to escape them.
  1. Combine with Other Operators:
  • Combine the LIKE operator with other operators such as AND or OR for more complex conditions.


The SQL LIKE operator proves to be an invaluable tool for crafting dynamic and flexible queries, allowing developers to perform pattern matching within textual data. Whether searching for specific words, validating data formats, or creating dynamic filters, the LIKE operator facilitates precise data retrieval. As you navigate the landscape of SQL, mastering the syntax, understanding wildcards, and adhering to best practices associated with the LIKE operator will empower you to leverage its potential effectively, unlocking powerful pattern-matching capabilities within your databases.

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