Preamble
PostgreSQL HAVING statement is used in combination with GROUP BY statement to limit groups of returned strings only to those whose condition is TRUE.
The syntax for the HAVING statement in PostgreSQL
SELECT expression1_id, expression2_id,. expression_n_id,
aggregate_function
FROM tabs
[WHERE conds]
GROUP BY expression1_id, expression2_id,... expression_n_id
HAVING cond;
Statement parameters and arguments
- aggregate_function – This can be an aggregate function such as sum, count, min, max, or avg.
- expression1_id, expression_2id,… expression_n_id – Expressions which are not contained in the aggregate function and must be included in the GROUP BY operator.
- WHERE conds – Optional. These are conditions for selecting records.
- HAVING cond – This is another condition applied only to aggregate results to limit groups of returned lines. Only those groups whose condition is evaluated as TRUE will be included in the result set.
Example using the sum function
Let’s consider a HAVING example that uses the sum function.
You can also use the sum function to return a department and the sum(salary) function to that department. The PostgreSQL statement HAVING will filter the results so that only departments with a total salary greater than 25000 USD will be returned.
SELECT depart, sum(salary) AS "Salaries for the department"
FROM empls
GROUP BY depart
HAVING sum(salary) > 25000;
Example using count function
Let’s see how to use the HAVING operator with the count function.
You can use the count function to return a department and the number of employees (for that department) that have “Active” status. The PostgreSQL statement HAVING will filter the results so that only departments with a maximum of 35 employees will be returned.
SELECT department, count(*) AS "Number of employees"
FROM empls
WHERE status = 'Active'
GROUP BY depart
HAVING count(*) <= 35;
Example using min function
Let’s now see how to use the HAVING operator with the min function.
You can also use the min function to return the name of each department and the minimum wage in that department. PostgreSQL operator HAVING returns only those departments where the minimum wage is less than 36000 USD.
SELECT depart, min(salary) AS "Lowest salary".
FROM empls
GROUP BY depart
HAVING min(salary) < 36000;
Example using max function
Finally, let’s consider how to use the HAVING operator with the max function.
For example, you can also use the max function to return the name of each department and the maximum salary of the department. PostgreSQL statement HAVING will return only those departments whose maximum salary is more or equal to 31950 USD.
SELECT depart, max(salary) AS "Highest salary"
FROM empls
GROUP BY depart
HAVING max(salary) >= 31950;
PostgreSQL: Group By Having | Course
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”