> ## Documentation Index
> Fetch the complete documentation index at: https://thenile.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Cube

> Provides a data type for multi-dimensional cubes.

The [cube](https://www.postgresql.org/docs/current/cube.html) extension in PostgreSQL provides a data type for multi-dimensional cubes. It is useful for applications requiring vector operations, such as geometric data, multi-dimensional indexing, and scientific computing.
Your Nile database arrives with `cube` extension already enabled, so there's no need to run `create extension`.

## Creating and Populating a Sample Table

Before creating the index, let's create a sample table and populate it with cube data:

```sql theme={null}
CREATE TABLE my_table (
    id SERIAL PRIMARY KEY,
    dimensions CUBE
);

INSERT INTO my_table (dimensions) VALUES
    ('(1,2,3)'),
    ('(4,5,6)'),
    ('(7,8,9)'),
    ('(10,11,12)'),
    ('(13,14,15)');
```

## Querying cube Data

With the `cube` extension, you can perform various operations on multi-dimensional data:

### Find Points within a Specific Range

```sql theme={null}
SELECT * FROM my_table WHERE dimensions <@ '(0,0,0),(5,5,5)';
```

This query returns all points within the cube defined by `(0,0,0)` to `(5,5,5)`.

### Compute the Distance Between Two Points

```sql theme={null}
SELECT cube_distance('(1,2,3)', '(4,5,6)');
```

This function computes the Euclidean distance between two cube points.

## Creating an Index on cube Columns

To optimize queries, you can create a GiST index:

```sql theme={null}
CREATE INDEX cube_idx ON my_table USING gist (dimensions);
```

This index improves performance for queries filtering cube data.

## Limitations

* The `cube` type supports up to 100 dimensions by default.
* It does not support operations like `+`, `-`, or `*` directly; you must use provided cube functions.
* Indexing performance depends on the number of dimensions and the dataset size.

## Removing a cube Index

If you need to remove an index:

```sql theme={null}
DROP INDEX cube_idx;
```

## Conclusion

The `cube` extension in PostgreSQL enables efficient storage and querying of multi-dimensional data. It is particularly useful for geometric and scientific applications where vector operations and spatial indexing are needed.

For more details, refer to the [PostgreSQL documentation](https://www.postgresql.org/docs/current/cube.html).