Preamble
Comparison operators are used in the WHERE sentence to determine which records to select. Here is a list of comparison statements that you can use in Oracle PL/SQL:
| Comparator operators | Description |
| = | Exactly |
| Whatever | |
| More than | |
| More or equal | |
| < | Less than |
| <= | Less or equal |
| IN ( ) |
Corresponds to the value on the list
|
| NOT | Negates the condition |
| BETWEEN | Within range (inclusive) |
| IS NULL | NULL value |
| IS NOT NULL | Value, not NULL |
| LIKE | Template matching % and _ |
| REGEXP_LIKE |
Comparison of templates with regular expressions
|
| EXISTS |
This condition is fulfilled if the subquery returns at least one line
|
Consider examples of comparison operators that you can use in Oracle PL/SQL.
Example of an equality operator
In Oracle PL/SQL you can use the = operator to verify equality in a query.
For example, you can use an = operator:
SELECT *
FROM contacts
WHERE last_name = 'Bernard';
In this example, the SELECT operator returns all the rows from the contacts table where last_name equals Bernard.
Here is an example of the inequality operator <>, !=
In Oracle PL/SQL, you can use the <> or != operators. To check inequality in a query.
For example, we could check for inequality using the <> operator in the following way:
SELECT *
FROM contacts
WHERE last_name <> 'Bernard';
In this example, the SELECT operator will return all the rows from the contacts table where last_name does not equal Bernard.
Or you may also write this query using the != operator in the following way:
SELECT *
FROM contacts
WHERE last_name != 'Bernard';
Both these requests will return the same results.
An example of an operator larger than >
You can use the > operator in Oracle PL/SQL to check the expression “more than”.
SELECT *
FROM contacts
WHERE contact_id > 20;
In this example, the SELECT statement will return all rows from the contacts table where contact_id is greater than 20. Contact_id equal to 20 will not be included in the result set.
Example operator greater than or equal to >=
In Oracle PL/SQL you can use the >= operator to check the expression, “more or equal”.
SELECT *
FROM contacts
WHERE contact_id >= 20;
In this case, the contact id must be higher than or equal to 20 for the SELECT operator to retrieve all records from the contacts table. Therefore in an instance, the resultant set will have the contact id value of 20.
The example of the operator is less than <
You can use the < operator in Oracle PL/SQL to check the expression “less than”.
SELECT *
FROM contacts
WHERE contact_id < 150;
In this example, the SELECT operator will return all rows from the contacts table where contact_id is less than 150. contact_id equal to 150 will not be included in the resulting set.
The example of the operator is less than or equal to <=
In Oracle PL/SQL you can use the <= operator to check for an expression that is “less or equal”.
SELECT *
FROM contacts
WHERE contact_id <= 150;
In this case, the SELECT operator will provide a list of all contacts database rows with contact id values of 150 or less. Therefore, for instance, the 150th product id will be a part of the final set.
Comparison Operators (Introduction to Oracle SQL)
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
How Can Biotechnology Companies Improve Database Performance for Genomics and Research Workloads?
- 21 September 2026
- Database Performance Management
Biotech companies may improve database performance by monitoring SQL activity, query latency, storage I/O, resource consumption, workload changes, database waits, and analytical processing in real time. Effective biotechnology database performance monitoring allows research and IT teams to identify bottlenecks, optimise inefficient queries, tackle data-intensive workloads and prepare infrastructure for increasing genomics and scientific data demands. … Continue reading “How Can Biotechnology Companies Improve Database Performance for Genomics and Research Workloads?”
How Can Cybersecurity Platforms Prevent Database Slowdowns During Authentication and Threat Detection Spikes?
You can monitor the behaviour of SQL activity, transaction latency, database waits, locks, resource usage, and query behaviour and spikes in workload to prevent database slowdowns during spikes in authentication and threat detection on cybersecurity platforms. Effective cybersecurity database performance monitoring allows IT teams to identify new bottlenecks, tune slow SQL, investigate unusual activity, and … Continue reading “How Can Cybersecurity Platforms Prevent Database Slowdowns During Authentication and Threat Detection Spikes?”
How Can Hospitals Optimize Cloud Databases Without Compromising Patient Care?
- 20 September 2026
- AIDatabase Performance Management
Hospitals can improve cloud database optimization for healthcare by continuously monitoring workloads, optimizing SQL, detecting anomalies, analyzing resource utilization, controlling cloud costs, and planning capacity before performance degrades. Effective hospital IT infrastructure monitoring helps protect EHR and clinical application responsiveness, while Enteros provides observability, AIOps, SQL intelligence, predictive analytics, and root cause analysis for proactive … Continue reading “How Can Hospitals Optimize Cloud Databases Without Compromising Patient Care?”
How Can BFSI Companies Use AIOps to Prevent Database Performance Failures?
BFSI companies can use AIOps to prevent database performance failures by combining continuous observability, anomaly detection, SQL analysis, predictive analytics, capacity planning, and automated root cause analysis. Effective BFSI database performance monitoring helps teams identify abnormal workloads before they become incidents, while Enteros supports proactive performance management across complex banking, financial services, and insurance environments. … Continue reading “How Can BFSI Companies Use AIOps to Prevent Database Performance Failures?”