LIKE Operator in SQL: Top 5 Best Usage

The LIKE operator in SQL is an important & powerful tool used to match a pattern in the query statement. It allows users to filter data using wildcard characters, which is especially useful for flexible text discoveries in large datasets. Here, we will deeply explore the LIKE operator, starting from syntax, benefits, real-world use cases with T-SQL queries, and 50 interview questions.

Introduction of LIKE Operator in SQL

The LIKE operator in SQL Server enables us to perform a partial string match using wildcards. We can use it if we need to find a specific pattern.

This operator uses two main wildcards:
🔹 % (percent): It shows zero or more characters.
🔹 _ (Undercore): Matches a character.

Syntax of LIKE operator:

SELECT <ColumnName1>,<ColumnName2>, ........<ColumnNameN> 
FROM <TableName>
WHERE <ColumnName> LIKE 'pattern';

A Glimpse into History

The Operator was introduced in SQL-86, the initial version of the SQL standard. Regular manifestations and patterns, such as those inspired by Unix, influenced its design. Over time, all major relational database systems (RDBMS), including SQL Server, Oracle, MySQL, and PostgreSQL, have adopted the operator, which is a universal tool for pattern-based filtering.

✅ Advantages of the LIKE Operator in SQL

Advantages of the LIKE Operator in SQL Server are given below:

🔹It Allows Flexible Pattern Matching

Allows searching for partial strings using wildcards (% and _), enabling powerful filtering capabilities.

🔹Easy to Use & Simple Syntax

Easy to understand, use and implement even for beginners, without needing complex regular expressions.

🔹Widely supported by almost all RDBMS.

Available in almost all relational database systems like SQL Server, MySQL, PostgreSQL, Oracle, etc.

🔹Ideal for Search Features

Perfect for implementing user-facing search fields where exact matches aren’t required.

🔹It is Useful for Data Validation

Helps in finding inconsistent or malformed data (e.g., emails not ending with .com).

🔹Easy to Combine with Other Conditions

We can use other operators (AND, OR, and other SQL operators) also with the LIKE operation to fulfill our requirements.

❌ Disadvantages of the LIKE Operator in SQL

A few disadvantages of the LIKE Operator in SQL are given below for more clarity:

🔸It may cause performance Issues on Large Datasets.

Patterns starting with % turn off index usage, leading to full table scans and slower performance.

🔸Case Sensitivity Can Vary Due to Collation Setting

Matching results depend on collation settings, which can lead to inconsistent behaviour across environments.

🔸It does not support Advanced Patterns.

Unlike regular expressions, LIKE cannot match complex string rules or character sets.

🔸Lack of Typo Tolerance

LIKE is strict in matching; it cannot handle misspellings or fuzzy matches.

🔸Risk of Unintended Matches

Poorly constructed patterns (like %_) may return more data than intended, affecting query accuracy.

🔸Inefficient for Frequent Searches

Not suitable for high-frequency, real-time search use cases in large applications—better alternatives exist like Full-Text Search.

🔐 Required Permission

Executing the LIKE operator does not require any special permissions beyond the standard SELECT privilege on the table. However, users must have access rights to the schema containing the table or view.

🔧 When the LIKE Operator in SQL is Needed

Use the LIKE operator when:

🔹 If you need flexible pattern matching.

🔹 If you’re creating a search feature.

🔹 If you want to filter data by prefix/suffix/mid-word matches.

🔹 If you’re performing data profiling or QA validations.

🔹 If you need to identify inconsistent or incorrect data formats.

✅ Best Practices for LIKE Operator In SQL

🔹 Try to avoid starting patterns with % to allow index usage.

🔹 Combine LIKE with LOWER() for case-insensitive search in case-sensitive collations.

🔹 Escape special characters when needed using the ESCAPE keyword.

🔹 We can use LEN() or CHARINDEX() if exact control is needed over string structure.

🔹 Prefer full-text search for complex searches over extensive data.

🧩 A few common problems with the LIKE Operator

A few common issues are given below:

Problem	Cause	Solution
Unexpected results	Due to misplaced wildcard	Review the query and correct the pattern.
Special characters treated as wildcards	% or _ in data.	Use the ESCAPE clause.
Index not used properly	Due to pattern starts with %	Avoid leading wildcards
Case sensitivity issue	Due to Collation setting	Use COLLATE Latin1_General_CI_AI or apply LOWER()

Common Problems with Like Operator

Top 20 Example of LIKE Operator in SQL

Top 20 Examples of LIKE Operator are given below:

Example – 1: Fetch a list of vendors whose name starts with Da

SELECT VendorID, VendorName, City
FROM Vendors WITH(nolock)
WHERE VendorName LIKE ‘Da%’;

Example – 2: Fetch a list of vendors whose name ends with ‘Sharma’

SELECT VendorID, VendorName, City, MobileNo,
FROM Vendors WITH(nolock)
WHERE VendorName LIKE ‘%Sharma’;

Example – 3: Fetch a list of companies whose name contains ‘Technologies’

SELECT CompanyName, CityName, YOE
FROM Companies WITH(nolock)
WHERE CompanyName LIKE ‘% Technologies%’;

Example – 4: CityName, one letter followed by ‘an’

SELECT CityName
FROM Cities WITH(nolock)
WHERE Name LIKE ‘_an’;

Example – 5: Fetch StudentName which starts with Su and ends with t

SELECT StudentName
FROM Students WITH(nolock)
WHERE StudentName LIKE ‘Su%t’;

Example – 6: Exactly 4-letter LoginName

SELECT LoginName
FROM Logins WITH(nolock)
WHERE LoginName LIKE ‘__‘;

Example – 7: Find a list of Emails with the domain name – ‘yahoo.com’

SELECT UserName, Email
FROM Users WITH(nolock)
WHERE Email LIKE ‘%@yahoo.com’;

Example – 8: Students’ First Name begins with [Dh] and the third letter is [i]

SELECT [StudentFirstName],
FROM Students WITH(nolock)
WHERE StudentFirstName LIKE ‘Dh_r%’;

Example – 9: Students’ Postal codes beginning with ’12’

SELECT StudentName, Address, PostalCode
FROM Addresses WITH(nolock)
WHERE PostalCode LIKE ‘12%’;

Example – 10: Product codes with ‘-2024’

SELECT ItemID, ItemName, ItemCode
FROM Items WITH(nolock)
WHERE ItemCode LIKE ‘%-2024’;

Conclusion

The LIKE operator in SQL is an essential and fundamental feature which provides a flexible pattern-based discoveries. Although its performance is limited, especially in large datasets, it remains a crucial tool for developers and DBAs in real-world applications. Understanding its syntax, wildcards, limitations, and best practices ensures optimised and accurate query results.