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Showing content from https://neon.com/postgresql/postgresql-tutorial/postgresql-like below:

PostgreSQL LIKE Operator

Summary: in this tutorial, you will learn how to use the PostgreSQL LIKE operators to query data based on patterns.

Suppose that you want to find customers, but you don’t remember their names exactly. However, you can recall that their names begin with something like Jen.

How do you locate the exact customers from the database? You can identify customers in the customer table by examining the first name column to see if any values begin with Jen. However, this process can be time-consuming, especially when the customer table has a large number of rows.

Fortunately, you can use the PostgreSQL LIKE operator to match the first names of customers with a string using the following query:

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name LIKE 'Jen%';

Output:

first_name | last_name
------------+-----------
 Jennifer   | Davis
 Jennie     | Terry
 Jenny      | Castro
(3 rows)

The WHERE clause in the query contains an expression:

first_name LIKE 'Jen%'

The expression consists of the first_name, the LIKE operator and a literal string that contains a percent sign (%). The string 'Jen%' is called a pattern.

The query returns rows whose values in the first_name column begin with Jen and are followed by any sequence of characters. This technique is called pattern matching.

You construct a pattern by combining literal values with wildcard characters and using the LIKE or NOT LIKE operator to find the matches.

PostgreSQL offers two wildcards:

Percent sign (%) matches any sequence of zero or more characters.
Underscore sign (_) matches any single character.

Here’s the basic syntax of the LIKE operator:

value LIKE pattern

The LIKE operator returns true if the value matches the pattern. To negate the LIKE operator, you use the NOT operator as follows:

value NOT LIKE pattern

The NOT LIKE operator returns true when the value does not match the pattern.

If the pattern does not contain any wildcard character, the LIKE operator behaves like the equal (=) operator.

Let’s take some examples of using the LIKE operator

The following statement uses the LIKE operator with a pattern that doesn’t have any wildcard characters:

SELECT 'Apple' LIKE 'Apple' AS result;

Output:

result
--------
 t
(1 row)

In this example, the LIKE operator behaves like the equal to (=) operator. The query returns true because ‘Apple' = 'Apple' is true.

The following example uses the LIKE operator to match any string that starts with the letter A:

SELECT 'Apple' LIKE 'A%' AS result;

Output:

result
--------
 t
(1 row)

The query returns true because the string 'Apple' starts with the letter 'A'.

We’ll use the customer table from the sample database:

The following example uses the LIKE operator to find customers whose first names contain the string er :

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name LIKE '%er%'
ORDER BY
  first_name;

Output:

first_name  |  last_name
-------------+-------------
 Albert      | Crouse
 Alberto     | Henning
 Alexander   | Fennell
 Amber       | Dixon
 Bernard     | Colby
...

The following example uses the LIKE operator with a pattern that contains both the percent (%) and underscore (_) wildcards:

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name LIKE '_her%'
ORDER BY
  first_name;

Output:

first_name | last_name
------------+-----------
 Cheryl     | Murphy
 Sherri     | Rhodes
 Sherry     | Marshall
 Theresa    | Watson
(4 rows)

The pattern _her% matches any strings that satisfy the following conditions:

The first character can be anything.
The following characters must be 'her'.
There can be any number (including zero) of characters after 'her'.

The following query uses the NOT LIKE operator to find customers whose first names do not begin with Jen:

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name NOT LIKE 'Jen%'
ORDER BY
  first_name;

Output:

first_name  |  last_name
-------------+--------------
 Aaron       | Selby
 Adam        | Gooch
 Adrian      | Clary
 Agnes       | Bishop
...

PostgreSQL ILIKE operator, which is similar to the LIKE operator, but allows for case-insensitive matching. For example:

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name ILIKE 'BAR%';

Output:

first_name | last_name
------------+-----------
 Barbara    | Jones
 Barry      | Lovelace
(2 rows)

In this example, the BAR% pattern matches any string that begins with BAR, Bar, BaR, and so on. If you use the LIKE operator instead, the query will return no row:

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name LIKE 'BAR%';

Output:

first_name | last_name
------------+-----------
(0 rows)

PostgreSQL also provides some operators that mirror the functionality of LIKE, NOT LIKE, ILIKE, NOT ILIKE, as shown in the following table:

Operator Equivalent ~~ LIKE ~~* ILIKE !~~ NOT LIKE !~~* NOT ILIKE

For example, the following statement uses the ~~ operator to find a customer whose first names start with the string Dar:

SELECT
  first_name,
  last_name
FROM
  customer
WHERE
  first_name ~~ 'Dar%'
ORDER BY
  first_name;

Output:

first_name | last_name
------------+-----------
 Darlene    | Rose
 Darrell    | Power
 Darren     | Windham
 Darryl     | Ashcraft
 Daryl      | Larue
(5 rows)

Sometimes, the data, that you want to match, contains the wildcard characters % and _. For example:

The rents are now 10% higher than last month
The new film will have _ in the title

To instruct the LIKE operator to treat the wildcard characters % and _ as regular literal characters, you can use the ESCAPE option in the LIKE operator:

string LIKE pattern ESCAPE escape_character;

Let’s create a simple table for demonstration:

CREATE TABLE t(
   message text
);

INSERT INTO t(message)
VALUES('The rents are now 10% higher than last month'),
      ('The new film will have _ in the title');

SELECT message FROM t;

Note that you’ll learn how to create a table and insert data into it in the upcoming tutorials.

Output:

message
----------------------------------------------
 The rents are now 10% higher than last month
 The new film will have _ in the title
(2 rows)

The following statement uses the LIKE operator with the ESCAPE option to treat the % followed by the number 10 as a regular character:

SELECT * FROM t
WHERE message LIKE '%10$%%' ESCAPE '$';

Output:

message
----------------------------------------------
 The rents are now 10% higher than last month
(1 row)

In the pattern %10$%%, the first and last % are the wildcard characters whereas the % appears after the escape character $ is a regular character.

Use the LIKE operator to match data by patterns.
Use the NOT LIKE operator to negate the LIKE operator.
Use the % wildcard to match zero or more characters.
Use the _ wildcard to match a single character.
Use the ESCAPE option to specify the escape character.
Use the ILIKE operator to match data case-insensitively.

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