Preamble
The Oracle/PLSQL TO_DATE function converts a string into a date.
Syntax of the Oracle/PLSQL TO_DATE function
TO_DATE( string1_id, [ format_mask_id ], [ nls_language_id ] )
Parameters and function arguments
- string1_id – is a string that will be converted to date.
- format_mask_id – is optional. This is the format that will be used to convert string1 to date.
It can be one or a combination of the following values:
| Parameter | Explanation |
| YYYY | 4-digit year. |
| YYY YY Y |
The last 3, 2 or 1 digit(s) of the year. |
| IYY IY I |
The last 3, 2 or 1 digit(s) of the ISO year. |
| IYYY | 4-digit year according to ISO standard. |
| RRRR |
Takes the year with 2 digits and returns the year with 4 digits.
The value between 0-49 will return 20xx year. Value between 50-99 will return 19xx year. |
| Q | Quarter of the year (1, 2, 3, 4; JAN-MAR = 1). |
| MM | Month (01-12; JAN = 01). |
| MON | Abbreviated name of the month. |
| MONTH |
The name of the month, supplemented by spaces up to 9 characters long.
|
| RM | Roman numeral RM (I-XII; JAN = I). |
| WW |
Week of the year (1-53), where week 1 begins on the first day of the year and continues until the seventh day of the year.
|
| W |
Week of the month (1-5), where the first week begins on the first day of the month and ends on the seventh.
|
| IW |
Week of the year (1-52 or 1-53) based on ISO standard.
|
| D | Day of the week (1-7). |
| DAY | The name of the day. |
| DD | Day of the month (1-31). |
| DDD | Day of the Year (1-366). |
| DY | Abbreviated name of the day. |
| J |
Julian day; number of days from 1 January 4712 BC.
|
| HH | One o’clock (1-12). |
| HH12 | One o’clock (1-12). |
| HH24 | One o’clock (0-23). |
| MI | One minute (0-59). |
| SS | Секунда (0-59). |
| SSSSS | Seconds after midnight (0-86399). |
| FF |
Fractional seconds. Use a value between 1 and 9 after FF to specify the number of digits in fractions of a second. For example, ‘FF4’.
|
| AM, A.M., PM, or P.M. | Meridian indicator. |
| AD or A.D | AD indicator. |
| BC or B.C. | BC indicator. |
| TZD | Summertime information. For example, ‘PST’ |
| TZH | The time zone is one hour. |
| TZM | The time zone is the minute. |
| TZR | The time zone of the region. |
- nls_language_id – is optional. NLS language is used to convert string1 to date.
The TO_DATE function can be used in the following versions of Oracle/PLSQL
Oracle 12c, Oracle 11g, Oracle 10g, Oracle 9i, Oracle 8i
Let’s consider some examples of the TO_DATE function to understand how to use the TO_DATE function in Oracle.
SELECT TO_DATE('2019/07/22', 'yyyyy/mm/dd') FROM DUAL;
--Result: 22.07.2019
SELECT TO_DATE('072219', 'MMDDYYY') FROM DUAL;
--Result: 22.07.2019
SELECT TO_DATE('20190722', 'yyyyymmdd') FROM DUAL;
--Result: 22.07.2019
SELECT TO_DATE('30.01.2019 18:30:52', 'DD.MM.YYYYY HH24:MI:SS') FROM DUAL;
--Result: 30.01.2019 18:30:52
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 Intelligent Database Analytics Improves Performance and Scalability in Modern Retail Platforms
- 13 May 2026
- Database Performance Management
Introduction Retail has undergone a dramatic transformation over the past decade. Today’s retailers operate in a digital-first economy where customers expect fast, personalized, and seamless shopping experiences across multiple channels. From e-commerce platforms and mobile apps to in-store point-of-sale systems and inventory management tools, every component of modern retail relies on efficient data infrastructure. At … Continue reading “How Intelligent Database Analytics Improves Performance and Scalability in Modern Retail Platforms”
How to Accelerate Insurance Sector Growth with Enteros Cost Attribution and RevOps Strategy
Introduction The insurance industry is rapidly evolving as organizations embrace digital transformation, data-driven decision-making, and customer-centric business models. Modern insurers must deliver seamless digital experiences, process claims efficiently, personalize policy offerings, and maintain operational agility in an increasingly competitive market. At the same time, insurance companies face rising operational costs, growing regulatory complexity, and increasing … Continue reading “How to Accelerate Insurance Sector Growth with Enteros Cost Attribution and RevOps Strategy”
How to Scale Entertainment Platforms with Enteros Cloud FinOps, AIOps, and Database Intelligence
Introduction The entertainment industry has entered a new era driven by digital streaming, cloud-native platforms, online gaming, live content delivery, and personalized audience experiences. Modern entertainment companies must support millions of users simultaneously while delivering seamless streaming, real-time interactions, and high-quality digital experiences across multiple devices. As entertainment platforms continue to expand globally, organizations face … Continue reading “How to Scale Entertainment Platforms with Enteros Cloud FinOps, AIOps, and Database Intelligence”
How to Transform Media Sector Growth with Enteros Database Optimization, AI SQL, and Generative AI
Introduction The media industry is evolving at an unprecedented pace. Streaming platforms, digital publishing, online advertising, social media engagement, and real-time content delivery are transforming how audiences consume media across the globe. Modern media organizations must deliver seamless digital experiences, personalized content recommendations, and uninterrupted streaming performance while managing massive volumes of data and growing … Continue reading “How to Transform Media Sector Growth with Enteros Database Optimization, AI SQL, and Generative AI”