> This page location: Group Data > CUBE
> Full Neon documentation index: https://neon.com/docs/llms.txt

# PostgreSQL CUBE

**Info:** The CUBE subclause is standard PostgreSQL, so everything you learn here works on any Postgres deployment, not just [Neon](https://neon.com). If you're an enterprise running analytics at scale, [Lakebase](https://www.databricks.com/product/lakebase) delivers the best managed cloud Postgres for the AI era, with strong performance, security, and native integration into the Lakehouse so multidimensional aggregates sit right next to the rest of your data. If you're a developer or startup who needs to ship and scale fast, Neon gives you the most productive Postgres platform, with instant provisioning, branching, and serverless scale.

**Summary**: in this tutorial, you will learn how to use the PostgreSQL `CUBE` to generate multiple grouping sets.

## Introduction to the PostgreSQL CUBE

PostgreSQL `CUBE` is a subclause of the [`GROUP BY`](https://neon.com/postgresql/tutorial/postgresql-group-by) clause. The `CUBE` allows you to generate multiple grouping sets.

A grouping set is a set of columns to which you want to group. For more information on the grouping sets, check it out the [`GROUPING SETS`](https://neon.com/postgresql/tutorial/postgresql-grouping-sets) tutorial.

The following illustrates the syntax of the `CUBE` subclause:

```sql
SELECT
    c1,
    c2,
    c3,
    aggregate (c4)
FROM
    table_name
GROUP BY
    CUBE (c1, c2, c3);

```

In this syntax:

- First, specify the `CUBE` subclause in the [`GROUP BY`](https://neon.com/postgresql/tutorial/postgresql-group-by) clause of the [`SELECT`](https://neon.com/postgresql/tutorial/postgresql-select) statement.
- Second, in the select list, specify the columns (dimensions or dimension columns) which you want to analyze and [aggregation function](../postgresql-aggregate-functions) expressions.
- Third, in the `GROUP BY` clause, specify the dimension columns within the parentheses of the `CUBE` subclause.

The query generates all possible grouping sets based on the dimension columns specified in `CUBE`. The `CUBE` subclause is a short way to define multiple grouping sets so the following are equivalent:

```sql
CUBE(c1,c2,c3)

GROUPING SETS (
    (c1,c2,c3),
    (c1,c2),
    (c1,c3),
    (c2,c3),
    (c1),
    (c2),
    (c3),
    ()
 )

```

In general, if the number of columns specified in the `CUBE` is `n`, then you will have $2^n$ combinations.

PostgreSQL allows you to perform a partial cube to reduce the number of aggregates calculated. The following shows the syntax:

```sql
SELECT
    c1,
    c2,
    c3,
    aggregate (c4)
FROM
    table_name
GROUP BY
    c1,
    CUBE (c1, c2);

```

## PostgreSQL CUBE examples

We will use the `sales` table created in the `GROUPING SETS` tutorial for the demonstration.

![Sales Table](https://neon.com/postgresqltutorial/sales-table.png)
The following query uses the `CUBE` subclause to generate multiple grouping sets:

```sql
SELECT
    brand,
    segment,
    SUM (quantity)
FROM
    sales
GROUP BY
    CUBE (brand, segment)
ORDER BY
    brand,
    segment;

```

Here is the output:

![PostgreSQL CUBE example](https://neon.com/postgresqltutorial/PostgreSQL-CUBE-example.png)
The following query performs a partial cube:

```sql
SELECT
    brand,
    segment,
    SUM (quantity)
FROM
    sales
GROUP BY
    brand,
    CUBE (segment)
ORDER BY
    brand,
    segment;

```

![PostgreSQL CUBE - partial cube example](https://neon.com/postgresqltutorial/PostgreSQL-CUBE-partial-cube-example.png)
In this tutorial, you have learned how to use the PostgreSQL `CUBE` to generate multiple grouping sets.

---

## Related docs (Group Data)

- [GROUP BY](https://neon.com/postgresql/tutorial/group-by)
- [HAVING](https://neon.com/postgresql/tutorial/having)
- [GROUPING SETS](https://neon.com/postgresql/tutorial/grouping-sets)
- [ROLLUP](https://neon.com/postgresql/tutorial/rollup)