Consider CUSTOMERS table has following records:
SQL> SELECT * FROM CUSTOMERS;
+----+----------+-----+-----------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 3 | kaushik | 23 | Kota | 2000.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+-----------+----------+
7 rows in set (0.00 sec) |
Here are simple examples showing usage of SQL Comparison Operators:
SQL> SELECT * FROM CUSTOMERS WHERE AGE >= 25 AND SALARY >= 6500;
+----+----------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+---------+
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+---------+---------+
2 rows in set (0.00 sec)
SQL> SELECT * FROM CUSTOMERS WHERE AGE >= 25 OR SALARY >= 6500;
+----+----------+-----+-----------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+-----------+----------+
5 rows in set (0.00 sec)
SQL> SELECT * FROM CUSTOMERS WHERE AGE IS NOT NULL;
+----+----------+-----+-----------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 3 | kaushik | 23 | Kota | 2000.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+-----------+----------+
7 rows in set (0.00 sec)
SQL> SELECT * FROM CUSTOMERS WHERE NAME LIKE 'Ko%';
+----+-------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+-------+-----+---------+---------+
| 6 | Komal | 22 | MP | 4500.00 |
+----+-------+-----+---------+---------+
1 row in set (0.00 sec)
SQL> SELECT * FROM CUSTOMERS WHERE AGE IN ( 25, 27 );
+----+----------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+---------+
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+---------+---------+
3 rows in set (0.00 sec)
SQL> SELECT * FROM CUSTOMERS WHERE AGE BETWEEN 25 AND 27;
+----+----------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+---------+
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+---------+---------+
3 rows in set (0.00 sec)
SQL> SELECT AGE FROM CUSTOMERS
WHERE EXISTS (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500);
+-----+
| AGE |
+-----+
| 32 |
| 25 |
| 23 |
| 25 |
| 27 |
| 22 |
| 24 |
+-----+
7 rows in set (0.02 sec)
SQL> SELECT * FROM CUSTOMERS
WHERE AGE > ALL (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500);
+----+--------+-----+-----------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+--------+-----+-----------+---------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
+----+--------+-----+-----------+---------+
1 row in set (0.02 sec)
SQL> SELECT * FROM CUSTOMERS
WHERE AGE > ANY (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500);
+----+----------+-----+-----------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+---------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+-----------+---------+
4 rows in set (0.00 sec)
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