# rank

> 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: rank
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/window-functions/rank
page-component-name: cloud-data-platform
page-version: master
page-component-version: master
page-component-title: Cloud
page-relative-src-path: sql/sql-functions/window-functions/rank.adoc
page-edit-url: https://github.com/redpanda-data/cloud-docs/edit/main/modules/reference/pages/sql/sql-functions/window-functions/rank.adoc
description: The `rank()` window function determines the rank of a value in a group of values, based on the ORDER BY expression in the OVER clause.
page-topic-type: reference
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/window-functions/rank.md -->

The `rank()` window function determines the rank of a value in a group of values, based on the `ORDER BY` expression in the `OVER` clause. It can be used with all [data types supported by Redpanda SQL](https://docs.redpanda.com/cloud-data-platform/reference/sql/sql-data-types/).

## [](#syntax)Syntax

The syntax for this function is:

```sql
RANK() OVER (
    [PARTITION BY partition_expression, ... ]
    ORDER BY sort_expression [ASC | DESC], ...
)
```

Rows with equal values for the ranking criteria receive the same rank. The output type for this function is `bigint` and it indicates the rank of values in a table, regardless of the input types.

-   If the optional `PARTITION BY` expression is present, the rankings are reset for each group of rows

-   If the `ORDER BY` expression is omitted then all ranks are equal to 1


## [](#parameters)Parameters

-   `()`: This function does not take any arguments, but the parentheses are required.


## [](#examples)Examples

The following examples use the `winsales` table that stores details about some sales transactions:

```sql
CREATE TABLE winsales(
    salesid int,
    dateid date,
    sellerid int,
    buyerid text,
    qty int,
    qty_shipped int);
INSERT INTO winsales VALUES
    (30001, '8/2/2003', 3, 'b', 10, 10),
    (10001, '12/24/2003', 1, 'c', 10, 10),
    (10005, '12/24/2003', 1, 'a', 30, null),
    (40001, '1/9/2004', 4, 'a', 40, null),
    (10006, '1/18/2004', 1, 'c', 10, null),
    (20001, '2/12/2004', 2, 'b', 20, 20),
    (40005, '2/12/2004', 4, 'a', 10, 10),
    (20002, '2/16/2004', 2, 'c', 20, 20),
    (30003, '4/18/2004', 3, 'b', 15, null),
    (30004, '4/18/2004', 3, 'b', 20, null),
    (30007, '9/7/2004', 3, 'c', 30, null);
```

### [](#rank-with-order-by)`rank()` with ORDER BY

This example executes the `rank()` function with `ORDER BY` keyword and calculates the rank of all rows based on the quantity sold:

```sql
SELECT salesid, qty,
    RANK() OVER (ORDER BY qty)
FROM winsales
ORDER BY 2,1;
```

Output that includes the sales ID along with the quantity sold and regular ranks:

```sql
 salesid | qty | rank
---------+-----+------
   10001 |  10 |    1
   10006 |  10 |    1
   30001 |  10 |    1
   40005 |  10 |    1
   30003 |  15 |    5
   20001 |  20 |    6
   20002 |  20 |    6
   30004 |  20 |    6
   10005 |  30 |    9
   30007 |  30 |    9
   40001 |  40 |   11
(11 rows)
```

### [](#rank-with-order-by-and-partition-by)`rank()` with ORDER BY and PARTITION BY

This example executes the `rank()` function with `ORDER BY` keyword and `PARTITION BY` clause, partitions the table by seller ID, orders each partition by the quantity, and assigns a rank to each row:

```sql
SELECT salesid, sellerid, qty,
    RANK() OVER (PARTITION BY sellerid ORDER BY qty)
FROM winsales
ORDER BY 2,3,1;
```

The query returns:

```sql
 salesid | sellerid | qty | rank
---------+----------+-----+------
   10001 |        1 |  10 |    1
   10006 |        1 |  10 |    1
   10005 |        1 |  30 |    3
   20001 |        2 |  20 |    1
   20002 |        2 |  20 |    1
   30001 |        3 |  10 |    1
   30003 |        3 |  15 |    2
   30004 |        3 |  20 |    3
   30007 |        3 |  30 |    4
   40005 |        4 |  10 |    1
   40001 |        4 |  40 |    2
(11 rows)
```