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How to Use LIKE in SQL: SQL Pattern Matching

SQL pattern matching is a very important and useful ability. In this article, we look at how you can perform it using LIKE in SQL.

SQL Pattern matching is a very simple concept. It allows you to search strings and substrings and find certain characters or groups of characters. Apart from SQL, this operation can be performed in many other programming languages.

In this article, we’ll examine how you can use LIKE in SQL to search substrings. We’ll also make the distinction between SQL exact match and SQL partial match by explaining how you can expand your search by using wildcards. Finally, we’ll clarify when you should use something other than LIKE to find a match.

How to Use LIKE in SQL?

Suppose you have to retrieve some records based on whether a column contains a certain group of characters. As you know, in SQL the WHERE clause filters SELECT results. By itself, WHERE finds exact matches. But what if you need to find something using a partial match?

In that case, you can use LIKE in SQL. This operator searches strings or substrings for specific characters and returns any records that match that pattern. (Hence the SQL pattern matching.) Below is the syntax of the LIKE operator in a SELECT statement:

SELECT   [ column_list |  *  ]   
FROM  table_name
WHERE  column or expression  LIKE  pattern;

Notice that the column name or the expression to be searched comes before LIKE in SQL. After the operator is the pattern to match. This pattern can be pure text or text mixed with one or more wildcards. We’ll explain the use of wildcards next.

SQL Partial Match: Using LIKE with Wildcards

If you don’t know the exact pattern you’re searching for, you can use wildcards to help you find it. Wildcards are text symbols that denote how many characters will be in a certain place within the string. The SQL ANSI standard uses two wildcards, percent (%) and underscore (_), which are used in different ways. When using wildcards, you perform a SQL partial match instead of a SQL exact match as you don’t include an exact string in your query.

wildcard description
% zero, one, or many characters, including spaces
_ a single character

Look at the complete animal table which will be used in our SQL queries:

id name
1 frog
2 dog
3 bear
4 fox
5 jaguar
6 puma
7 panda
8 lion
9 leopard
10 sheep
11 camel
12 monkey
13 lemur
14 rabbit
15 hedgehog
16 elephant
17 elephant.. .
18 langur
19 hog
20 gerenuk
21
22 null

Note: .. . denotes two spaces.

SQL Partial Match: the Percent Wildcard

As you can see in the above table, the percent wildcard can be used when you’re not sure how many characters will be part of your match. In the example below, notice what happens when you use only this wildcard with LIKE in SQL:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '%' ;

Result:

id name
1 frog
2 dog
3 bear
4 fox
5 jaguar
6 puma
7 panda
8 lion
9 leopard
10 sheep
11 camel
12 monkey
13 lemur
14 rabbit
15 hedgehog
16 elephant
17 elephant.. .
18 langur
19 hog
20 gerenuk
21

Note: .. . denotes two spaces.

This use of the SQL partial match returns all the names from the animal table, even the ones without any characters at all in the name column. This is because the percent wildcard denotes any character or no characters. Even when there is a null value in the name column, an empty string is returned.

But if you would like to return only the animal names that start with a “g”, you should write the query using a “g” in front of the percent wildcard:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE 'g%' ;

The result of this SQL partial match operation is the following:

id name
20 gerenuk

Similarly, if you would like to select the animal names that end with a “g”, you’d put the percent wildcard first, as shown in this SQL partial match query:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '%g';

Result:

id name
1 frog
2 dog
15 hedgehog
19 hog

The following query returns all animals whose name contains a “g”. To do this, use two percent wildcards and a “g” character, as shown below.

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '%g%';

Result:

id name
1 frog
2 dog
5 jaguar
15 hedgehog
18 langur
19 hog
20 gerenuk

All these animals have a name that contains a “g” somewhere – at the beginning, in the middle, or at the end.

Now, let’s move on to the underscore wildcard.

SQL Partial Match: the Underscore Wildcard

The underscore wildcard represents a single character for each underscore. In this SQL partial match, it can replace any character at all, but each underscore is limited to one character. Look at the example below:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '_';

Result:

id name

0 rows

This query didn’t return any records because there are no single-character animal names in the table.

The next example displays all names that contain exactly five characters. To represent this, we must use five underscores:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '_____';

Result:

id name
7 panda
10 sheep
11 camel
13 lemur

If you use the underscore wildcard at the end of your SQL partial match string, the query will return every record that matches the given text plus one more character. Below we see an example:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE 'lio_';

Result:

id name
8 lion

What is returned when the query has an underscore wildcard in the middle of the string?

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE 'p_ma';

Result:

id name
6 puma

It is all animals whose names start with “p” and end with “ma”, with only one character in between.

SQL Partial Match: Combining Wildcards

You can also use a combination of underscore and percent wildcards for your SQL pattern matching. Look at the following example:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '%ho_';

Result:

id name
15 hedgehog
19 hog

As you can see, this query returned names that combined “ho” with any number of characters in front and only one character following.

UsingLIKE in SQL with Text

Now we will discuss how to use LIKE in SQL with text-only strings and no wildcards. In some circumstances, you may find that there are better options than using LIKE in SQL pattern matching. But for now, let’s see how this works. We’ll start by looking at the complete table of animal names and ID numbers, as shown below:

id name
1 frog
2 dog
3 bear
4 fox
5 jaguar
6 puma
7 panda
8 lion
9 leopard
10 sheep
11 camel
12 monkey
13 lemur
14 rabbit
15 hedgehog
16 elephant
17 elephant. ..
18 langur
19 hog
20 gerenuk
21
22 null

Note: . .. denotes two spaces.

Note that the record where id=21 has an empty string (without any characters). The last record has a NULL value in the name column.

Now, say we want to retrieve the records where the animal’s name is “elephant”. That’s pretty simple, as the example below shows:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE 'elephant';

Result:

id name
16 elephant

In the table, there are actually two records containing “elephant”. However, the second record has an additional two spaces at the end of the word, so it isn’t returned.

Let’s try another text pattern that includes these two spaces.

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE 'elephant  ';

Result:

id name
17 elephant. ..

Note: . .. denotes two spaces.

Again, there is only one record: “elephant” with two spaces.

Next, suppose we use a concrete text string and an equals operator (=), like this:

SELECT 
  id, 
  name 
FROM animal
WHERE name = 'elephant '  ;

Result:

id name
16 elephant

If you want to check if a text string is the same as the value of a column, you’re looking for a SQL exact match rather than a SQL partial match. In that case, use an equals operator rather than LIKE.

Combining NOT and LIKE Operators

You can also test for strings that do not match a pattern. To do this, we combine the LIKE and NOT operators. It is another way of performing the SQL pattern matching.

In the example below, we want to find all animal names that don’t have an “a” character:

SELECT 
  id, 
  name 
FROM animal
WHERE name NOT LIKE '%a%';

Result:

id name
1 frog
2 dog
4 fox
8 lion
10 sheep
12 monkey
13 lemur
15 hedgehog
19 hog
20 gerenuk
21 camel

Using LIKE in SQL with Other Operators

The WHERE clause can include more than one condition. Therefore, LIKE and NOT LIKE can be used with other operators. Let’s look at another example:

SELECT 
  id, 
  name 
FROM animal
WHERE name LIKE '%g'  OR name LIKE 's%'  ;

Result:

id name
1 frog
2 dog
10 sheep
15 hedgehog
19 hog

It returned all the animal names that start with an “s” character or end with a “g” character.

Using LIKE in SQL in Other Statements

So far, we’ve discussed using LIKE in SQL only in SELECT statements. But this operator can be used in other statements, such as UPDATE or DELETE. As you can see, the syntax is quite similar:

UPDATE table 
SET column1 = newValue
WHERE  column2  LIKE  pattern ;
DELETE  FROM  table
WHERE  column  LIKE  pattern ;

Let’s see how we can use LIKE to change some animal names. Ready?

UPDATE  animal 
SET name='tiger'
WHERE name LIKE '%key%' ;

There is only one record that matches the LIKE %key% condition: monkey. After this update, “tiger” will replace all instances of “monkey”.

Here’s the result after we update and then select all records from the animal table.

SELECT * 
FROM  animal ;
id name
1 frog
2 dog
3 bear
4 fox
5 jaguar
6 puma
7 panda
8 lion
9 leopard
10 sheep
11 camel
12 tiger
13 lemur
14 rabbit
15 hedgehog
16 elephant
17 elephant.. .
18 langur
19 hog
20 gerenuk
21
22 null

Note: . .. denotes two spaces.

Next, we’ll delete any records where the animal name starts with a “t”:

DELETE FROM animal
WHERE name LIKE 't%'  ;

To Learn More About SQL Pattern Matching

SQL pattern matching is very useful for searching text substrings. LIKE and its close relative NOT LIKE make this quite easy to do. If you are interested in learning more about pattern matching and the LIKE operator, check out the SQL Basics course. It will show you how to build queries from scratch, but it will also introduce practical skills like pattern matching matching.

If you have a basic knowledge of SQL, you can refresh it with the SQL Practice Set of 88 exercises, ranging from simple tasks with SELECT FROM statements to more advanced problems involving multiple subqueries. Try both of the courses now for free!

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