Preamble
PostgreSQL MAX function returns the maximum value of the expression.
Syntax of the max function in PostgreSQL
SELECT max(aggregate_expression_id)
FROM tabs
[WHERE conds];
Or the syntax of the max function when grouping results into one or more columns:
SELECT expression1_id,2_id,..._n_id,
max(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 max function and must be included in the GROUP BY operator at the end of the SQL query.
- aggregate_expression_id – This is the column or expression from which the maximum 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 conditions – Optional. These are the conditions that must be met to select records.
The max 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
Let’s look at some examples of max functions to understand how to use max in PostgreSQL.
For example, you might want to select all entries with a maximum quantity from an inventory table as max(quantity) AS “Highest Quantity”.
SELECT max(quantity) AS "Highest Quantity"
FROM inventory;
In this example of the max function, we added the expression max(quantity) AS “Highest Quantity”. As a result, “Highest Quantity” will be displayed as the field name when the result set is returned.
Example using GROUP BY
In some cases, you will need to use the GROUP BY operator with the max function.
For example, you can also use the max function to return a department and the maximum quantity from the inventory table.
SELECT depart, max(quantity) AS "Highest Quantity"
FROM inventory
GROUP BY depart;
Since your SELECT operator has one column that is not encapsulated in the max function, you should use the GROUP BY operator. That’s why the department field shall 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
How to Achieve Real Estate Cost Transparency with Enteros: AI SQL Analytics and AIOps Platform Intelligence
- 17 February 2026
- Database Performance Management
Introduction Real estate has evolved into a technology-driven industry. From digital property marketplaces and smart building platforms to tenant apps, CRM systems, leasing automation tools, and investment analytics dashboards—modern real estate enterprises depend on complex data ecosystems. Every lease agreement, rent payment, occupancy report, maintenance request, and investor presentation is powered by databases running behind … Continue reading “How to Achieve Real Estate Cost Transparency with Enteros: AI SQL Analytics and AIOps Platform Intelligence”
How to Optimize SaaS Performance and RevOps Efficiency with Enteros: Database Management and Cloud FinOps Intelligence
Introduction The SaaS business model promises scalable growth, recurring revenue, and predictable expansion. But behind every subscription dashboard, billing workflow, in-app analytics panel, and customer success metric lies a powerful—and often overlooked—engine: The database layer. In today’s technology sector, SaaS companies compete on speed, reliability, personalization, and cost efficiency. Every millisecond of latency impacts user … Continue reading “How to Optimize SaaS Performance and RevOps Efficiency with Enteros: Database Management and Cloud FinOps Intelligence”
What Telecom CIOs Should Know About AI SQL, Cost Attribution, and Predictive Cloud FinOps with Enteros
- 16 February 2026
- Database Performance Management
Introduction The telecommunications industry operates at a scale few sectors can match. Billions of call detail records (CDRs).Real-time 5G traffic management.Subscriber billing systems.Network performance analytics.IoT connectivity platforms.Streaming, messaging, roaming, and edge computing services. Behind every one of these services lies a complex, high-volume database ecosystem. And as telecom providers modernize into cloud-native, multi-cloud, and hybrid … Continue reading “What Telecom CIOs Should Know About AI SQL, Cost Attribution, and Predictive Cloud FinOps with Enteros”
How Enteros Combines Generative AI and Database Intelligence to Drive Predictable Revenue Operations Growth
Introduction Revenue Operations (RevOps) has evolved from a coordination function into a strategic growth engine. Modern enterprises rely on tightly integrated sales, marketing, finance, customer success, and product systems to generate predictable revenue. But behind every CRM update, pricing calculation, renewal forecast, pipeline report, and customer usage metric lies a critical foundation: The database layer. … Continue reading “How Enteros Combines Generative AI and Database Intelligence to Drive Predictable Revenue Operations Growth”