Preamble
In this tutorial you will learn how to use literals (text, integers and numbers) in Oracle with examples.
In Oracle, he wrote the same thing as the constant. We will consider three types of literals: text literals, integer literals, numeric literals and date/time literals.
Text literals
Text literals are always enclosed in single quotes (‘).
For example:
'King Arthur'
'23-FEB-18'
Integer liters
Integer literals can contain up to 38 digits.
Integer literals can be either positive numbers or negative numbers. If you do not specify a sign, a positive number is assumed. Here are some examples of real integer literals:
18
+18
-18
Numerical literals
Numerical literals can contain up to 38 digits. Numerical literals can be both positive and negative. If you do not specify a character, a positive number is assumed. Here are some examples of acceptable numeric literals:
23
+23
-23
23e-04
23.607
-23.607
Literals date/time
Date and time are in single quotes (‘).
For example:
'23.02.1918' -- the date when the interventionists were (historical)
'14.01.2018 08:13:24'
When using date/time values, use the TO_DATE function to convert literals to dates.
For example:
SELECT TO_DATE('14.01.2018', 'dd.mm.yyyy') FROM dual;
TO_DATE('14.01.2018', 'DD.MM.YYYY').
----------------------------------
14.01.2018
In this example, the function will take a literal value ‘14.01.2018’ and convert it to a date.
What is the use of literals in oracle database
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 Enterprises Reduce Database Costs Without Sacrificing Performance?
- 11 September 2026
- Database Performance Management
Enterprises can reduce database costs without sacrificing performance by identifying inefficient SQL, right-sizing infrastructure, eliminating unused capacity, analyzing workload patterns, improving storage efficiency, and using database observability to connect resource consumption with application performance. Database cost optimization helps organizations control infrastructure spending while Enteros UpBeat provides performance intelligence, workload visibility, predictive analytics, and Cloud FinOps … Continue reading “How Can Enterprises Reduce Database Costs Without Sacrificing Performance?”
How Can AI Detect Database Performance Anomalies Before They Cause Downtime?
AI can detect database performance anomalies by continuously analyzing workload patterns, SQL behavior, latency, resource usage, waits, and historical baselines. AI database anomaly detection helps identify unusual behavior before it becomes a larger outage. With Enteros UpBeat, IT teams can detect emerging issues earlier, investigate root causes faster, and improve database reliability across complex enterprise … Continue reading “How Can AI Detect Database Performance Anomalies Before They Cause Downtime?”
How Can Financial Institutions Detect Database Bottlenecks Before Transaction Delays Occur?
- 10 September 2026
- Database Performance Management
Financial institutions can detect database bottlenecks before transaction delays occur by continuously monitoring query latency, database waits, CPU, memory, I/O, locking, workload changes, and transaction throughput. By combining performance baselines, anomaly detection, SQL intelligence, predictive analytics, and automated root cause analysis, teams can identify emerging issues early and optimize databases before customer-facing banking, payment, or … Continue reading “How Can Financial Institutions Detect Database Bottlenecks Before Transaction Delays Occur?”
What Role Does AI-Powered Database Monitoring for Banking Play in Performance Management?
AI-powered database monitoring for banking helps financial institutions detect anomalies, identify performance bottlenecks, analyse SQL workloads, predict capacity risks, and accelerate troubleshooting. By combining database observability with automated analysis, AI-powered database performance supports faster incident response, more reliable transactions, better resource utilisation, stronger capacity planning, and smarter cloud cost decisions across increasingly complex banking database … Continue reading “What Role Does AI-Powered Database Monitoring for Banking Play in Performance Management?”