MySQL FIND_IN_SET Explained: How to Search Comma-Separated Values Correctly

1. Introduction

The Challenge of Searching Comma-Separated Data in MySQL

When working with databases, you may encounter cases where multiple values are stored in a single column separated by commas. For example, a column may contain a string like "1,3,5", and you may want to extract only the records that include the value “3”.

In such cases, using the standard = operator or the IN clause often does not produce the expected results. This is because a comma-separated string is treated as a single string value, meaning comparisons are evaluated against the entire string rather than individual elements within it.

What Is the FIND_IN_SET Function?

In situations like this, the MySQL FIND_IN_SET function becomes very useful.
This function allows you to easily determine whether a specified value exists within a comma-separated string.

For example, consider the following SQL statement:

SELECT * FROM users WHERE FIND_IN_SET('3', favorite_ids);

In this query, you can extract records where the comma-separated string in the favorite_ids column (e.g., "1,2,3,4") contains the value “3”.

Purpose of This Article and Target Audience

This article explains how to use the FIND_IN_SET function from the basics in a clear and structured way. From basic syntax to practical examples, comparisons with other search methods, important considerations, and FAQs, this guide provides practical knowledge for real-world development.

This article is intended for:

• Web engineers and backend developers who regularly use MySQL
• Developers who must work with existing systems that store comma-separated data
• SQL beginners struggling with partial matching and value-based searches

2. Basic Syntax and Behavior of the FIND_IN_SET Function

Syntax of FIND_IN_SET

FIND_IN_SET is a MySQL function used to determine whether a specific value exists within a comma-separated string. The basic syntax is as follows:

FIND_IN_SET(search_value, comma_separated_string)

For example:

SELECT FIND_IN_SET('3', '1,2,3,4'); -- Result: 3

In this example, since “3” appears in the third position, the function returns the numeric value 3.

Return Value Rules

The FIND_IN_SET function behaves according to the following rules:

Example (Returning Position)

SELECT FIND_IN_SET('b', 'a,b,c'); -- Result: 2

Example (Value Not Found)

SELECT FIND_IN_SET('d', 'a,b,c'); -- Result: 0

Example (NULL Included)

SELECT FIND_IN_SET(NULL, 'a,b,c'); -- Result: NULL

Example Usage in a WHERE Clause

This function is most commonly used for filtering within a WHERE clause.

SELECT * FROM users WHERE FIND_IN_SET('admin', roles);

In this example, only rows where the roles column contains the string “admin” will be returned. If the column contains a value like "user,editor,admin", it will match.

Important Notes on Numbers and Strings

FIND_IN_SET performs comparisons as strings, which means it behaves as follows:

SELECT FIND_IN_SET(3, '1,2,3,4');     -- Result: 3
SELECT FIND_IN_SET('3', '1,2,3,4');   -- Result: 3

Although it works with both numeric and string values, unclear data types may lead to unexpected behavior. Therefore, it is best practice to handle values explicitly as strings whenever possible.

3. Practical Examples

Searching in a Column That Stores Comma-Separated Strings

In real-world systems, you may find cases where multiple values (such as IDs or permissions) are stored in a single column as a comma-separated string. For example, consider the following users table.

When you want to “retrieve users that include 3,” the FIND_IN_SET function is extremely convenient.

SELECT * FROM users WHERE FIND_IN_SET('3', favorite_ids);

Running this SQL will return the records for “Taro” and “Jiro”.

Works Fine Even When Values Look Numeric

Even when favorite_ids appears to contain numbers, FIND_IN_SET performs string-based comparisons, so it is safest to pass the argument as a string with quotes.

-- OK
SELECT * FROM users WHERE FIND_IN_SET('5', favorite_ids);

-- Works, but strictly speaking not recommended
SELECT * FROM users WHERE FIND_IN_SET(5, favorite_ids);

To keep queries readable and behavior predictable, it is recommended to explicitly specify the value as a string.

Dynamic Searches (Placeholders and Variables)

When generating SQL dynamically from a web application, it is common to use variables or bind parameters.

If you use a MySQL variable, it looks like this:

SET @target_id = '3';
SELECT * FROM users WHERE FIND_IN_SET(@target_id, favorite_ids);

When binding from an application layer (such as PHP, Python, or Node.js), you can handle it similarly using placeholders.

How to Handle Searching for Multiple Values

Unfortunately, FIND_IN_SET can only search for one value at a time.
If you want to retrieve records that contain “3 or 4,” you must write it multiple times using OR.

SELECT * FROM users
WHERE FIND_IN_SET('3', favorite_ids) OR FIND_IN_SET('4', favorite_ids);

If conditions become more complex, you should either dynamically build the SQL in your application or consider migrating to a normalized table structure.

4. Comparing FIND_IN_SET with Other Search Methods

Common Alternatives: IN and LIKE

In MySQL, besides FIND_IN_SET, you may also see the IN clause or the LIKE clause used to check whether a value is included. However, each method behaves differently, and using the wrong one can result in incorrect query results.

Here, let’s clarify how they differ from FIND_IN_SET and when to use each approach.

Comparison with the IN Clause

The IN clause is typically used to check whether a value matches one of multiple constant values.

-- Example of IN (this does NOT search inside "favorite_ids" for the value 3)
SELECT * FROM users WHERE favorite_ids IN ('3');

In this case, only records where favorite_ids is an exact match for “3” will be returned. That means values like "1,3,5" will not match—only a row where the column value is exactly "3" will match.

By contrast, FIND_IN_SET checks the position of an element within a comma-separated list, allowing you to accurately retrieve records that include “3” like this:

SELECT * FROM users WHERE FIND_IN_SET('3', favorite_ids);

✅ Key usage guideline:

• IN: Use with normalized tables (e.g., SELECT * FROM posts WHERE category_id IN (1, 3, 5))
• FIND_IN_SET: Use with denormalized comma-separated strings

Comparison with the LIKE Clause

Technically, you can use LIKE for partial matching, but it comes with important pitfalls.

-- A common mistake with LIKE
SELECT * FROM users WHERE favorite_ids LIKE '%3%';

This query does not truly mean “contains the value 3”—it matches any string that contains the character “3”, meaning it may incorrectly match "13", "23", or "30".

This makes it impossible to reliably detect whether 3 exists as a standalone value.

✅ Key usage guideline:

• LIKE: Useful for fuzzy text searches, but cannot recognize comma-separated boundaries
• FIND_IN_SET: Accurately checks for standalone value matches inside comma-separated lists

Performance Differences

In particular, FIND_IN_SET cannot use indexes and often triggers full table scans. If you are working with large datasets, you may need to rethink the schema.

5. Important Notes and Best Practices

Not Compatible with Values Containing Commas

The FIND_IN_SET function assumes a simple list of values separated by commas. Therefore, if an individual element in the list itself contains a comma, the function will not behave as intended.

Incorrect Example:

SELECT FIND_IN_SET('1,2', '1,2,3,4'); -- Result: 1

Using it this way can produce incorrect matches because the entire string is evaluated improperly.
You should only use this function when you can guarantee that individual values do not contain commas.

Performance Concerns

Because FIND_IN_SET cannot use indexes, it performs a full table scan. As a result, when used on large tables, query performance may degrade significantly.

Workarounds:

• Instead of storing comma-separated values, normalize the relationship and manage it in a separate table.
• In performance-critical environments, consider temporary table expansion or JOIN-based strategies.

For example, if you create an intermediate table such as user_favorites, you can take advantage of indexes for faster searches:

SELECT users.*
FROM users
JOIN user_favorites ON users.id = user_favorites.user_id
WHERE user_favorites.favorite_id = 3;

Readability and Maintainability

Although FIND_IN_SET may seem convenient, it comes with several drawbacks:

• Queries are not intuitive (it returns position values)
• Adding or removing values is cumbersome
• Data integrity is difficult to enforce (multiple meanings in a single column)

Therefore, when maintainability and data integrity are important, revising the schema itself is often the best practice.

When You Must Use FIND_IN_SET

There are situations where you have no choice but to work with comma-separated columns—such as legacy systems or third-party products. In such cases, consider the following precautions:

• Apply other filtering conditions first to reduce the search scope
• Prevent formatting errors such as double commas or leading/trailing spaces
• Perform supplementary processing at the application layer when possible

6. Frequently Asked Questions (FAQ)

Can FIND_IN_SET Use Indexes?

No, FIND_IN_SET cannot use indexes. Internally, it splits and evaluates the string, so it does not benefit from MySQL’s index optimization.

As a result, using it on large tables may slow down query performance. For performance-critical systems, consider redesigning the schema or normalizing the data.

Does It Work Correctly with Mixed Numbers and Strings?

Generally, yes—but keep in mind that comparisons are performed as strings. If numeric and string values are mixed, unexpected behavior may occur.

For example, both of the following return a match for 3:

SELECT FIND_IN_SET(3, '1,2,3,4');     -- Result: 3
SELECT FIND_IN_SET('3', '1,2,3,4');   -- Result: 3

However, in cases like FIND_IN_SET('03', '01,02,03'), leading-zero formatting may affect matching behavior.
It is safest to standardize value formatting.

How Can I Search for Multiple Values at Once?

Because FIND_IN_SET only accepts a single search value, if you want to search for records containing “3 or 4,” you must call it multiple times using OR:

SELECT * FROM users
WHERE FIND_IN_SET('3', favorite_ids)
   OR FIND_IN_SET('4', favorite_ids);

If conditions become more complex, consider dynamically constructing SQL at the application layer or migrating to a normalized table structure.

FIND_IN_SET Is Causing Performance Issues. What Should I Do?

The following strategies are effective:

• Switch to a normalized table design
• Apply filtering conditions first to reduce the search scope
• Use it only when dealing with small datasets
• Consider migrating to structured formats such as full-text search or JSON data types

Modern MySQL versions support JSON data types. For example, if you manage the roles column as a JSON array, you can use JSON_CONTAINS() for flexible and efficient searches.

Will FIND_IN_SET Become Deprecated in the Future?

As of MySQL 8.0, FIND_IN_SET is not officially deprecated. However, denormalized data structures (comma-separated columns) are not recommended, so the practical use of this function is expected to decrease over time.

When redesigning your database, it is ideal to adopt normalized structures or JSON-based designs.

7. Conclusion

Reviewing the Features and Advantages of FIND_IN_SET

The FIND_IN_SET function is extremely useful in MySQL when searching comma-separated strings. It is especially helpful when you need to extract records that contain a specific value within a single column storing multiple values.

With its simple syntax, it enables checks for standalone value matches that are difficult to achieve accurately with the LIKE or IN clauses. This ability to detect distinct elements within a comma-separated list is its greatest strength.

Important Considerations When Using It

At the same time, there are several limitations and important considerations, so it should not be overused without careful thought:

• Indexes cannot be used (which may slow down searches)
• Not compatible with values that contain commas
• Assumes a denormalized structure
• Only supports single-value searches (multiple searches require OR conditions)

Understanding these characteristics is essential to using the function appropriately.

When You Should — and Should Not — Use It

How to Apply This in Practice

• Understand it as a flexible tool for working within existing database structures
• Use it as a reference point when deciding whether to adopt normalized data design in the future
• Rather than using it as a quick fix, clearly understand what the function actually does

For developers who prioritize maintainability and readability, it is best to think of this as a function that you may “use temporarily—but eventually graduate from.”