# Google Cloud BigQuery Dataset

Google Cloud BigQuery is a service that provides a relational database that is optimized for analytical workloads. It is a good choice for storing data that is relational in nature.

Nais provides BigQuery for storing and working with analytical datasets as a
managed service through Google Cloud Platform. This page describes how to get
started with BigQuery for your applications.

## Nais Application yaml manifest options

Full documentation of all available options can be found over at: [`spec.gcp.bigQueryDatasets[]`](/workloads/application/reference/spec.md#gcpbigquerydatasets).

## Caveats

**Automatic Deletion**

Once a BigQuery Dataset is provisioned, it will not be automatically deleted - unless one explicitly sets [`spec.gcp.bigQueryDatasets[].cascadingDelete`](/workloads/application/reference/spec.md#gcpbigquerydatasetscascadingdelete) to `true`.
Clean up is done by deleting application resource and deleting the BigQuery instance directly in [console.cloud.google.com](https://console.cloud.google.com/bigquery).
<br/>
When there exist no tables in the specified BigQuery Dataset, deleting the "nais application" will delete the whole BigQuery Dataset, even if [`spec.gcp.bigQueryDatasets[].cascadingDelete`](/workloads/application/reference/spec.md#gcpbigquerydatasetscascadingdelete) is set to `false`.

**Unique names**

The name of your Dataset must be unique within your team's GCP project.

**Updates/Immutability**

The NAIS Manifest does not currently support updating any setting of existing BigQuery Datasets.

**K8s resource naming**

Since Kubernetes does not permit underscores (`_`) in the names of any K8s resource, any underscores will be converted to hyphens (`-`).

## Example with all configuration options

See [full example](/workloads/application/reference/example.md).