Preamble
PostgreSQL to_char function converts a number or date to a string.
Syntax of to_char function in PostgreSQL
to_char( value, format_mask )
Parameters and function arguments
- value – A number, a date to be converted to a string.
- format_mask – The format that will be used to convert the value to a string. The format_mask is different from whether you convert numbers or dates. Let’s have a look.
- WITH NUMBERS – With format_mask numbers can be one of the following and can be used in many combinations:
| Parameter | Explanation |
| 9 | Value (without initial zeroes) |
| 0 | Value (with leading zeros) |
| . | Decimal |
| , | Group splitter |
| PR | A negative value in angle brackets |
| С | Symbol |
| L | Symbol of currency |
| D | Decimal |
| G | Group splitter |
| MI | Minus sign (for negative numbers) |
| PL | Sign plus (for positive numbers) |
| SG | A plus/minus sign (for positive and negative numbers) |
| RN | Roman numerals |
| TH | Serial number suffix |
| th | Serial number suffix |
| V | Shift in numbers |
| EEEE | Scientific notation |
With dates
With dates, format_mask can be one of the following and can be used in many combinations.
| Parameter | Explanation |
| YYYY | 4-digit year |
| Y,YYY | 4-digit semicolon year |
| YYY YY Y |
Last 3, 2 or 1 digit (and) years |
| IYYY | The 4-digit year according to ISO standard |
| IYY IY I |
Last 3, 2 or 1 digit(s) of ISO year |
| Q | A quarter of the year (1, 2, 3, 4; JAN-MAR = 1) |
| ММ | Month (01-12; JAN = 01) |
| MON | Abbreviated name of the month in upper case |
| Mon | Abbreviated name of the month with a capital letter |
| mon | Abbreviated name of the month in lower case |
| MONTH | The name of the month in capital letters, completed with spaces up to 9 characters long |
| Month | The name of the month with a capital letter, supplemented with spaces up to 9 characters long |
| month | The name of the month in lowercase letters, supplemented with spaces up to 9 characters long |
| RM | One month with Roman numerals |
| rm | Month in lowercase Roman numerals |
| WW | Week of the year (1-53), where week 1 begins on the first day of the year |
| W | Week of the month (1-5), where week 1 begins on the first day of the month |
| IW | ISO Week of the year (01-53) |
| DAY | The name of the day in capital letters, completed with spaces up to 9 characters long |
| Day | The name of the day with a capital letter, completed with spaces up to 9 characters long |
| day | The name of the day in lowercase letters, completed with spaces up to 9 characters long |
| DY | Abbreviated name of the day in upper case |
| Dy | Abbreviated name of the day with a capital letter |
| dy | Abbreviated name of the day in lowercase letters |
| DDD | Day of the year (1-366) |
| IDDD | Day of the year based on ISO year |
| DD | Day of the month (01-31) |
| D | Day of the week (1-7, where 1 = Sunday, 7 = Saturday) |
| ID | Day of the week based on ISO year (1-7, where 1 = Monday, 7 = Sunday) |
| J | Julian day; the number of days from midnight November 24, 4714 BC. |
| HH | One o’clock of the day (01-12) |
| HH12 | One o’clock of the day (01-12) |
| HH24 | One o’clock of the day (00-23) |
| MI | One minute (00-59) |
| SS | One second (00-59) |
| MS | Millisecond (000-999) |
| US | Microsecond (000000-999999) |
| SSSS | Seconds after midnight (0-86399) |
| am, AM, pm, or PM | Meridian Indicator |
| a.m., A.M., p.m., or P.M. | Meridian Indicator |
| ad, AD, a.d., or A.D | AD indicator |
| bc, BC, b.c., or B.C. | BC Indicator |
| TZ | Name of the time zone in upper case |
| tz | Name of the time zone in lower case |
| CC | 2-digit century |
The to_char 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 take a look at some examples of to_char functions to see how to_char can be used in PostgreSQL.
Example with numbers
Below are numerical examples of the to_char function.
SELECT to_char(1918, '9999.99');
--Result: 1918.00
SELECT to_char(1814.7, '9G999.99');
--Result: 1,814.70
SELECT to_char(1810.7, 'L9G999.99'); -Result: 1,814.70;
--Result: $ 1,810.70
SELECT to_char(1810.7, 'L9G999');
--Result: $ 1,811
SELECT to_char(141, '9 9 9');
--Result: 1 4 1
SELECT to_char(123, '00999');
--Result: 00123
Example with dates
Below are examples of the dates of the to_char function.
SELECT to_char(date '2019-04-23', 'YYYY/MM/DD');
--Result: 2019/04/23
SELECT to_char(date '2019-04-23', 'MMDDYY');
--Result: 042319
SELECT to_char(date '2019-04-23', 'Month DD, YYYYY');
--Result: April 23, 2019
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 Predictive Database Analytics Enables Smarter Capacity Planning
- 29 July 2026
- Software Engineering
Introduction Enterprise databases are growing faster than ever. Organizations are processing millions of transactions, managing petabytes of data, and supporting mission-critical applications across hybrid and multi-cloud environments. Whether it’s a banking platform handling real-time payments, a healthcare application processing patient records, or an e-commerce platform preparing for seasonal traffic spikes, database capacity planning has become … Continue reading “How Predictive Database Analytics Enables Smarter Capacity Planning”
How to Optimize Logistics and Warehouse Operations with Enteros Database Software, AI-Powered Analytics, and Database Observability
Introduction The logistics and warehousing industry has become the backbone of the global economy. E-commerce growth, omnichannel retail, same-day delivery expectations, global supply chain complexity, and increasing customer demands require logistics providers to process millions of transactions every day with exceptional speed and accuracy. Whether managing warehouses, coordinating transportation, tracking shipments, optimizing inventory, or fulfilling … Continue reading “How to Optimize Logistics and Warehouse Operations with Enteros Database Software, AI-Powered Analytics, and Database Observability”
Using FinOps and AI-Powered Analytics to Eliminate Cloud Database Cost Overruns
- 28 July 2026
- Software Engineering
Introduction Cloud adoption has transformed the way enterprises build, deploy, and scale applications. Organizations across banking, healthcare, retail, telecommunications, manufacturing, and SaaS increasingly rely on cloud databases to support mission-critical workloads, enable digital transformation, and deliver exceptional customer experiences. While cloud platforms provide flexibility and scalability, they also introduce a significant challenge—uncontrolled database costs. Cloud … Continue reading “Using FinOps and AI-Powered Analytics to Eliminate Cloud Database Cost Overruns”
How AIOps and Database Observability Improve SLA Compliance for Enterprise Applications
Introduction In today’s digital-first economy, enterprise applications power nearly every critical business process—from online banking and e-commerce platforms to healthcare systems, ERP applications, and customer service portals. Organizations promise customers and stakeholders high availability, rapid response times, and consistent application performance through Service Level Agreements (SLAs). However, meeting strict SLA targets has become increasingly challenging. … Continue reading “How AIOps and Database Observability Improve SLA Compliance for Enterprise Applications”