# Overview

> For the complete documentation index, see [llms.txt](https://docs.redpanda.com/llms.txt). Component-specific: [cloud-data-platform-full.txt](https://docs.redpanda.com/cloud-data-platform-full.txt)

---
title: Overview
latest-operator-version: v26.1.4
latest-console-tag: v3.7.3
latest-connect-version: 4.93.0
latest-redpanda-tag: v26.1.9
docname: sql/sql-functions/aggregate-functions/index
page-component-name: cloud-data-platform
page-version: master
page-component-version: master
page-component-title: Cloud
page-relative-src-path: sql/sql-functions/aggregate-functions/index.adoc
page-edit-url: https://github.com/redpanda-data/cloud-docs/edit/main/modules/reference/pages/sql/sql-functions/aggregate-functions/index.adoc
description: Aggregate functions compute a single result from a set of input values.
page-git-created-date: "2026-05-26"
page-git-modified-date: "2026-05-26"
---

<!-- Source: https://docs.redpanda.com/cloud-data-platform/reference/sql/sql-functions/aggregate-functions.md -->

Aggregate functions compute a single result from a set of input values. Redpanda SQL supports the following aggregate functions:

| Function Name | Description |
| --- | --- |
| sum() | Calculates and returns the sum of all values |
| min() | Calculates and returns the minimum value |
| for_min() | Calculates and returns a value corresponding to the minimal metric in the same row from a set of values |
| max() | Calculates and returns the maximum value |
| for_max() | Calculates and returns a value corresponding to the maximum metric in the same row from a set of values |
| avg() | Calculates and returns the average value |
| count() | Counts the number of rows |
| bool_and() | Calculates the boolean of all the boolean values in the aggregated group. FALSE if at least one of aggregated rows is FALSE |
| bool_or() | Calculates the boolean of all the boolean values in the aggregated group. TRUE if at least one of aggregated rows is TRUE |
| Function qualifier | Description |
| --- | --- |
| DISTINCT | Allows aggregation functions to operate on a distinct set of values within a column |

> 💡 **TIP**
>
> You can utilize the aggregate functions with the `GROUP BY` and `HAVING` clauses in the `SELECT` statement.