Preamble
The min function in PostgreSQL returns the minimum value of the expression.
Syntax of the min function in PostgreSQL
SELECT min(aggregate_expression_id)
FROM tabs
[WHERE conds];
Or the syntax of the min function when grouping the results into one or more columns:
SELECT expression1_id,2_id,..._n_id,
min(aggregate_expression_id)
FROM tabs
[WHERE conds]
GROUP BY expression1_id,2_id,..._n_id;
Parameters and arguments of the function
- expression1_id, expression2_id,… expression_n_id – Expressions that are not enclosed in the min function and must be included in the GROUP BY operator at the end of the SQL query.
- aggregate_expression_id – This is a column or expression from which the minimum value will be returned.
- tabs – These are the tables from which you want to get the records. At least one table must be specified in the FROM operator.
- WHERE conds – Optional. These are the conditions that must be met to select records.
The min 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.
Single Expression Example
Consider some examples of min functions to understand how to use the min function in PostgreSQL.
For example, you can find out how the minimum value is in the inventory table.
SELECT min(quantity) AS "Lowest Quantity"
FROM inventory;
In this example of the min function, we called the expression min(quantity) as “Lowest Quantity”. As a result, “Lowest Quantity” will be displayed as the field name when the result set returns.
Example using GROUP BY
In some cases, you will need to use GROUP BY operator with min function.
For example, you can also use the min function to return values in the department field and the min(quantity) field from the inventory table.
SELECT department, min(quantity) AS "Lowest Quantity"
FROM inventory
GROUP BY department;
Since your SELECT operator has one column that is not encapsulated in the min function, you must use the GROUP BY operator. That is why the department field should be specified in the GROUP BY operator.
PostgreSQL: Calculating Min, Max; Average
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
Intelligent Healthcare Performance Management: Enteros’ AIOps and Cloud FinOps Framework
- 18 December 2025
- Database Performance Management
Introduction Healthcare organizations are under unprecedented pressure to deliver better patient outcomes while managing rising operational costs, increasing regulatory demands, and rapidly expanding digital infrastructure. From electronic health records (EHRs) and telemedicine platforms to clinical analytics, revenue cycle management systems, and AI-assisted diagnostics, modern healthcare relies on highly complex, data-driven technology ecosystems. As these systems … Continue reading “Intelligent Healthcare Performance Management: Enteros’ AIOps and Cloud FinOps Framework”
How Enteros Transforms Retail Performance Management with AI-Driven Cost Estimation
Introduction The retail industry is operating in one of the most demanding digital environments in history. Omnichannel commerce, real-time inventory visibility, hyper-personalized customer journeys, dynamic pricing, and always-on digital storefronts have become non-negotiable expectations. Behind these seamless experiences lies a highly complex IT ecosystem powered by cloud platforms, SaaS databases, analytics engines, and microservices architectures. … Continue reading “How Enteros Transforms Retail Performance Management with AI-Driven Cost Estimation”
Driving Retail Excellence: How Enteros Delivers Intelligent Performance Management for SaaS Database Environments
- 17 December 2025
- Database Performance Management
Introduction The retail industry is evolving faster than any other sector in the digital economy. Omnichannel commerce, real-time inventory visibility, hyper-personalized customer experiences, subscription-based business models, and AI-powered analytics have become table stakes for modern retailers. Behind all of this innovation lies a complex web of SaaS applications, cloud-native platforms, and high-performance databases. Retailers now … Continue reading “Driving Retail Excellence: How Enteros Delivers Intelligent Performance Management for SaaS Database Environments”
Driving Healthcare Growth with Enteros: Optimizing Database Performance and Cloud FinOps for High-Impact Technology Operations
Introduction Healthcare organizations are experiencing a historic shift toward digital-first operations. Electronic Health Records (EHRs), telemedicine platforms, AI-powered diagnostics, patient engagement applications, research databases, and real-time analytics systems are now foundational to modern care delivery. At the heart of this transformation lies one critical dependency: high-performing, cost-efficient, and reliable databases operating at scale. However, as … Continue reading “Driving Healthcare Growth with Enteros: Optimizing Database Performance and Cloud FinOps for High-Impact Technology Operations”