# Custom databases

A word on naming

Different warehouses have different names for *logical databases*. The information in this document covers "databases" on Snowflake, Redshift, and Postgres; "projects" on BigQuery; and "catalogs" on Databricks Unity Catalog.

The values `project` and `database` are interchangeable in BigQuery project configurations.

## Configuring custom databases

The logical database that dbt models are built into can be configured using the `database` model configuration. If this configuration is not supplied to a model, then dbt will use the database configured in the active target from your `profiles.yml` file. If the `database` configuration *is* supplied for a model, then dbt will build the model into the configured database.

The `database` configuration can be supplied for groups of models in the `dbt_project.yml` file, or for individual models in model SQL files.

### Configuring database overrides in `dbt_project.yml`:

This config changes all models in the `jaffle_shop` project to be built into a database called `jaffle_shop`.

dbt\_project.yml

```yaml
name: jaffle_shop

models:
  jaffle_shop:
    +database: jaffle_shop

    # For BigQuery users:
    # project: jaffle_shop
```

### Configuring database overrides in a model file

This config changes a specific model to be built into a database called `jaffle_shop`.

models/my\_model.sql

```sql

{{ config(database="jaffle_shop") }}

select * from ...
```

### generate\_database\_name

The database name generated for a model is controlled by a macro called `generate_database_name`. This macro can be overridden in a dbt project to change how dbt generates model database names. This macro works similarly to the [generate\_schema\_name](./custom-schemas.md#advanced-custom-schema-configuration) macro.

To override dbt's database name generation, create a macro named `generate_database_name` in your own dbt project. The `generate_database_name` macro accepts two arguments:

1. The custom database supplied in the model config
2. The node that a custom database is being generated for

The default implementation of `generate_database_name` simply uses the supplied `database` config if one is present, otherwise the database configured in the active `target` is used. This implementation looks like this:

get\_custom\_database.sql

```jinja2
{% macro generate_database_name(custom_database_name=none, node=none) -%}

    {%- set default_database = target.database -%}
    {%- if custom_database_name is none -%}

        {{ default_database }}

    {%- else -%}

        {{ custom_database_name | trim }}

    {%- endif -%}

{%- endmacro %}
```

💡 Use Jinja's whitespace control to tidy your macros!

When you're modifying macros in your project, you might notice extra white space in your code in the `target/compiled` folder.

You can remove unwanted spaces and lines with Jinja's [whitespace control](../../faqs/Jinja/jinja-whitespace.md) by using a minus sign. For example, use `{{- ... -}}` or `{%- ... %}` around your macro definitions (such as `{%- macro generate_schema_name(...) -%} ... {%- endmacro -%}`).

### Managing different behaviors across packages

See docs on macro `dispatch`: ["Managing different global overrides across packages"](../../reference/dbt-jinja-functions/dispatch.md)

## Considerations

### BigQuery

When dbt opens a BigQuery connection, it will do so using the `project_id` defined in your active `profiles.yml` target. This `project_id` will be billed for the queries that are executed in the dbt run, even if some models are configured to be built in other projects.

## Related docs

* [Customize dbt models database, schema, and alias](../../guides/customize-schema-alias.md?step=1) to learn how to customize dbt models database, schema, and alias
* [Custom schema](./custom-schemas.md) to learn how to customize dbt model schema
* [Custom aliases](./custom-aliases.md) to learn how to customize dbt model alias name

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