In MySQL, the LIKE operator is used to search for a specified pattern for a column in a WHERE clause .

LIKE Syntax

SELECT column_name
FROM table_name
WHERE column_name LIKE pattern;

We have a table "employee" as below:

    employee

    id  first_name               salary       country
    .......................................................
    1   John                     10000         Canada
    2   Chris                    20000         California
    3   Max                      30000         London
    4   Jenny                    25000         Canada

LIKE Operator Examples

The below statement selects all employee with "country" starting with the "c" alphabet in the "employee" table:

SELECT * FROM employee
WHERE country LIKE 'c%';

Result

    id  first_name               salary       country
    .......................................................
    1   John                     10000         Canada
    2   Chris                    20000         California
    4   Jenny                    25000         Canada

The below statement selects all employee with "country" ending with the "n" alphabet in the "employee" table:

SELECT * FROM employee
WHERE country LIKE '%n';

Result

    id  first_name               salary       country
    .......................................................
    3   Max                      30000         London

The below statement selects all employee with "country" containing pattern "can" in the "employee" table:

SELECT * FROM employee
WHERE country LIKE '%can%';

Result

    id  first_name               salary       country
    .......................................................
    1   John                     10000         Canada
    4   Jenny                    25000         Canada

To get the records that do not match with the specified pattern we use NOT keyword as below:

SELECT * FROM employee
WHERE country NOT LIKE '%can%';

Result

    id  first_name               salary       country
    .......................................................
    2   Chris                    20000         California
    3   Max                      30000         London

Hope this will help you :)