Preamble
The current_time function in PostgreSQL returns the current time with the time zone.
Syntax of the current_time function in PostgreSQL
current_time( [ precision ] )
Parameters and function arguments
- It is optional. A number of digits for rounding to fractional seconds.
Note:
- The current_time function will return the current time of day in ‘HH:MM:SS.US+TZ’ format.
- Do not put parentheses () after current_time function if the precision parameter is not specified.
The current_time function can be used in future versions of PostgreSQL
|
PostgreSQL 11, PostgreSQL 10, PostgreSQL 9.6, PostgreSQL 9.5, PostgreSQL 9.4, PostgreSQL 9.3, PostgreSQL 9.2, PostgreSQL 9.1, PostgreSQL 9.0, PostgreSQL 8.4.
|
Let’s look at some examples of the current_time function to see how to use the current_time function in PostgreSQL.
For example:
SELECT current_time;
--Result: 11:08:46.339427+03:00
SELECT current_time(1);
--Result: 11:09:09.400000+03:00
SELECT current_time(2);
--Result: 11:09:30.580000+03:00
SELECT current_time(3);
--Result: 11:09:51.858000+03:00
Date functions in PostgreSQL, Time functions in PostgreSQL
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
Building Resilient BFSI Applications with Predictive AIOps and FinOps Intelligence
- 23 August 2026
- Database Performance Management
Introduction The Banking, Financial Services, and Insurance (BFSI) industry is undergoing a rapid digital transformation. Mobile banking, digital payments, online lending, insurance platforms, wealth management applications, and real-time financial services now depend on highly available and scalable IT infrastructure. Customers expect BFSI applications to be fast, secure, and available around the clock. Even a short … Continue reading “Building Resilient BFSI Applications with Predictive AIOps and FinOps Intelligence”
How AIOps and FinOps Enable Smarter Cloud Cost Optimization in Banking
Introduction Banking has entered an era where cloud technology is central to digital transformation. Mobile banking applications, digital payments, online lending, fraud detection, open banking APIs, wealth management platforms, and real-time financial services all depend on highly available and scalable IT infrastructure. Cloud adoption gives banks the flexibility to scale resources as demand changes, but … Continue reading “How AIOps and FinOps Enable Smarter Cloud Cost Optimization in Banking”
How to Improve Insurance Operations with Enteros Database Software, AI-Powered Analytics, and Database Observability
Introduction Insurance companies operate some of the most data-intensive business processes in the financial services industry. Policy administration, underwriting, claims, billing, customer portals, fraud detection, actuarial analysis, and regulatory reporting all depend on reliable data infrastructure. The insurance industry is also undergoing rapid digital transformation. Customers increasingly expect instant policy quotes, digital claims, mobile applications, … Continue reading “How to Improve Insurance Operations with Enteros Database Software, AI-Powered Analytics, and Database Observability”
How to Optimize Healthcare Database Performance with Enteros Database Software, AI-Powered Analytics, and Database Observability
Introduction Healthcare organizations are becoming increasingly dependent on digital infrastructure. Electronic Health Records (EHRs), patient portals, telemedicine platforms, medical imaging, laboratory systems, pharmacy applications, revenue cycle systems, payer platforms, and AI-powered clinical applications all rely on databases to deliver information quickly and reliably. As healthcare organizations consolidate data and move more workloads to cloud and … Continue reading “How to Optimize Healthcare Database Performance with Enteros Database Software, AI-Powered Analytics, and Database Observability”