String Functions

Text data is everywhere—names, emails, addresses, comments, logs, and more. Whether you’re cleaning up messy inputs, formatting data for reports, or extracting patterns, PostgreSQL’s string functions give you the tools you need to work with text efficiently and effectively.

In this article, we’ll look at what PostgreSQL string functions are, why they matter, and how they’re used in real-world applications.

What Are String Functions in PostgreSQL?

String functions are built-in operations that let you manipulate and analyze text values in your database. These functions can transform strings, measure length, match patterns, extract or replace substrings, and format output.

Since strings are one of the most common data types, these functions are used in nearly every database project—from basic search queries to advanced data transformation pipelines.

Why Are String Functions Useful?

PostgreSQL string functions help you:

• Clean and normalize data for consistency

• Parse input values or break text into parts

• Format strings for display in reports or exports

• Search for matches, patterns, or keywords in text

• Validate or filter records based on string conditions

These capabilities reduce the need for application-side processing and make your queries more powerful and self-contained.

Common Use Cases

Here are a few examples of how string functions are used in practice:

• Trimming spaces from user-submitted input like names or emails

• Extracting parts of a string like a domain from an email or a country code from a phone number

• Changing case for consistency in sorting or display

• Searching logs or comments for keywords or patterns

• Generating summaries or combining multiple fields for export or display

No matter the industry, string functions are essential for cleaning, organizing, and interpreting text-based data.

What You’ll Learn in This Section

This section of the documentation covers the most widely used string functions and operations in PostgreSQL. Topics include:

• LENGTH – Count the number of characters in a string

• SUBSTRING – Extract part of a string based on position

• UPPER / LOWER – Convert text to uppercase or lowercase

• TRIM – Remove whitespace or other characters from the edges

• LPAD / RPAD – Pad strings with characters to a fixed length

• CONCAT / CONCAT_WS – Combine multiple strings into one

• LIKE / ILIKE – Pattern matching for filtering or searching

• REGEXP_MATCHES / REGEXP_REPLACE – Use regular expressions for advanced string logic

• SPLIT_PART – Break a string into parts by a delimiter

• TO_CHAR – Convert numbers or dates to formatted strings

Each function will include syntax examples and practical use cases, so you can start applying them to your own data immediately.