Preamble
PostgreSQL random function can be used to return a random number or a random number within a range.
Syntax of the random PostgreSQL function
random( )
Parameters and function arguments
- There are no parameters or arguments for the random function.
Note:
- The random function will return a value from 0 (inclusive) to 1 (excluding), so the value will be in the range >= 0 and <1.
- Use the set seed function to set the initial value for random.
- The random function returns a completely random number if no initial number is set (the initial value is set by the set seed function).
- The random function will return a repeatable sequence of random numbers every time a specific initial value is used (the initial value is set using the set seed function).
Random decimal range
To create a random decimal number between two values (range), you can use the following formula:
SELECT random()*(b-a)+a;
Where a is the smallest number, and b is the largest number for which you want to generate a random number.
SELECT random()*(25-10)+10;
The above formula will generate a random decimal number >= 10 and < 25. (Note: this formula will never return 25 because random will never return 1).
Random range of integers
To create a random integer between two values (range), you can use the following formula:
SELECT floor(random()*(b-a+1))+a;
Where a is the smallest number, and b is the largest number for which you want to generate a random number.
SELECT floor(random()*(25-10+1))+10;
The above formula will generate a random integer from 10 to 25 inclusive.
The random function can be used in the following PostgreSQL versions
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.
Example of a random number
Let’s see how to use the random function in PostgreSQL to generate a random number >= 0 and < 1. For example:
SELECT random();
-Result: 0.0186054138466716
Although the random function will return a value above 0, it will never return a value of 1. It will always return a value below 1.
Example of a random decimal range
Let’s see how to use the PostgreSQL random function to generate a random decimal number between two numbers (i.e.: range).
For example, the next one will generate a random decimal value that >= 1 and < 10 (Note: it will never return 10):
SELECT random()*(10-1)+1;
--Result: 1.40731927193701
In the following example, a random decimal value >= 25 and < 40 will be generated (Note: it will never return 40):
SELECT random()*(40-25)+25;
--Result: 33.7993366038427
Example of a random integer range
Let’s see how to use the random function in PostgreSQL to generate a random integer between two numbers (i.e.: including the range).
For example, the next one will generate a random integer value from 1 to 10:
SELECT floor(random()*(10-1+1))+1;
--Result: 6
In the following example, a random integer value between 25 and 40 will be generated:
SELECT floor(random()*(40-25+1))+25;
--Result: 28
PostgreSQL: Generate 1000 Rows
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 to Optimize Media and Entertainment Database Performance with Enteros Database Software, AI-Powered Analytics, and Database Observability
- 30 August 2026
- Database Performance Management
Introduction The media and entertainment industry has become a digital-first business. Streaming services, digital publishing, online gaming content, advertising platforms, social experiences, content management systems, subscription platforms, and personalized recommendations all depend on databases. Modern media companies process enormous volumes of customer, content, advertising, transaction, and behavioral information. Read more”Indian Country” highlights Enteros and its … Continue reading “How to Optimize Media and Entertainment Database Performance with Enteros Database Software, AI-Powered Analytics, and Database Observability”
How to Optimize Manufacturing Database Performance with Enteros Database Software, AIOps, and Predictive Analytics
Introduction Manufacturing is becoming increasingly dependent on digital infrastructure. Modern factories use enterprise resource planning (ERP), manufacturing execution systems (MES), supply-chain platforms, warehouse management systems, industrial IoT, quality management applications, predictive maintenance, and advanced analytics to manage production. Behind these systems are databases processing enormous amounts of operational information. Production schedules, inventory levels, machine data, … Continue reading “How to Optimize Manufacturing Database Performance with Enteros Database Software, AIOps, and Predictive Analytics”
The Future of Industry-Specific Cloud Optimization with AIOps, FinOps, and AI-Powered Database Management
- 28 August 2026
- Database Performance Management
Introduction Cloud computing has become a foundational component of digital transformation across industries. Banking organizations use cloud platforms to support digital payments and online banking. Healthcare providers rely on cloud infrastructure for digital health applications and patient services. Educational institutions operate learning management systems and virtual classrooms in the cloud. Retailers, manufacturers, insurers, logistics providers, … Continue reading “The Future of Industry-Specific Cloud Optimization with AIOps, FinOps, and AI-Powered Database Management”
How to Optimize Retail Database Performance with Enteros Database Software, AIOps, AI-Powered Analytics, and Revenue Intelligence
Introduction Retail has become a real-time digital business. Ecommerce, mobile applications, point-of-sale systems, inventory platforms, loyalty programs, customer analytics, supply chain systems, recommendation engines, and payment platforms all depend on databases. Retailers also experience highly variable demand. Read more”Indian Country” highlights Enteros and its database performance management platform *Black Friday, holiday shopping, product launches, flash … Continue reading “How to Optimize Retail Database Performance with Enteros Database Software, AIOps, AI-Powered Analytics, and Revenue Intelligence”