> For the complete documentation index, see [llms.txt](https://v2.dataos.info/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://v2.dataos.info/concepts/resources/vulcan/configurations/engines/bigquery.md).

# BigQuery

Google BigQuery is a serverless cloud data warehouse that runs SQL on Google's infrastructure. Vulcan runs against BigQuery to manage transformations with version control and gated deployments.

## Local or built-in scheduler

**Engine adapter type**: `bigquery`

### Prerequisites

1. A Google Cloud Platform (GCP) project with BigQuery enabled
2. A service account with appropriate permissions (or OAuth credentials)
3. A service account key file (JSON format) for authentication

### Permissions

Vulcan requires the following BigQuery permissions:

* `bigquery.datasets.create`: to create datasets (schemas)
* `bigquery.tables.create`: to create tables and views
* `bigquery.tables.getData`: to read data from tables
* `bigquery.tables.updateData`: to insert, update, and delete data
* `bigquery.jobs.create`: to run queries

The `BigQuery Data Editor` and `BigQuery Job User` roles provide these permissions.

### Connection options

All the connection parameters you can use when setting up a BigQuery gateway:

| Option    | Description                                                                                |  Type  | Required |
| --------- | ------------------------------------------------------------------------------------------ | :----: | :------: |
| `type`    | Engine type name. Must be `bigquery`                                                       | string |     Y    |
| `method`  | Authentication method (`service-account`, `oauth`, `oauth-secrets`, `application-default`) | string |     Y    |
| `project` | The GCP project ID where BigQuery resources are located                                    | string |     Y    |
| `keyfile` | Path to the service account JSON key file (required for `service-account` method)          | string |     N    |

### Service account key file

The `keyfile` is a JSON key file downloaded from the Google Cloud Console:

1. Go to **IAM & Admin → Service Accounts**
2. Select your service account (or create a new one)
3. Go to the **Keys** tab
4. Click **Add Key → Create new key**
5. Select **JSON** and click **Create**

The downloaded file has the following structure:

```json
{
  "type": "service_account",
  "project_id": "<your-project-id>",
  "private_key_id": "<key-id>",
  "private_key": "-----BEGIN PRIVATE KEY-----\n<private-key-content>\n-----END PRIVATE KEY-----\n",
  "client_email": "<service-account-name>@<project-id>.iam.gserviceaccount.com",
  "client_id": "<client-id>",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://oauth2.googleapis.com/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/<service-account-name>",
  "universe_domain": "googleapis.com"
}
```

### Authentication methods

* **Service account** (`service-account`): requires `keyfile` path to JSON key file.
* **OAuth** (`oauth`): OAuth-based authentication.
* **OAuth secrets** (`oauth-secrets`): OAuth with secrets.
* **Application default** (`application-default`): uses default application credentials.

### Docker images

The following Docker images are available for running Vulcan with BigQuery:

| Image                               | Description                          |
| ----------------------------------- | ------------------------------------ |
| `tmdcio/vulcan-bigquery:0.228.1.10` | Main Vulcan API service for BigQuery |

Pull the images:

```bash
docker pull tmdcio/vulcan-bigquery:0.228.1.10
```

### Materialization strategy

BigQuery uses the following materialization strategies depending on the model kind:

| Model kind                  | Strategy                                | Description                                                                                                                                                                            |
| --------------------------- | --------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `INCREMENTAL_BY_TIME_RANGE` | DELETE by time range, then INSERT       | Vulcan first deletes existing records within the target time range, then inserts the new data. This ensures data consistency and prevents duplicates when reprocessing time intervals. |
| `INCREMENTAL_BY_UNIQUE_KEY` | MERGE ON unique key                     | Vulcan uses BigQuery's MERGE statement to update existing records based on the unique key or insert new ones if they do not exist.                                                     |
| `INCREMENTAL_BY_PARTITION`  | DELETE by partitioning key, then INSERT | Vulcan deletes existing records matching the partitioning key, then inserts the new data. This ensures partition-level consistency when reprocessing data.                             |
| `FULL`                      | CREATE OR REPLACE TABLE                 | Vulcan uses BigQuery's `CREATE OR REPLACE TABLE` statement to rebuild the table from scratch each time.                                                                                |

**Learn more about materialization strategies:**

* [INCREMENTAL\_BY\_TIME\_RANGE](/concepts/resources/vulcan/components/model/model_kinds.md#materialization-strategy)
* [INCREMENTAL\_BY\_UNIQUE\_KEY](/concepts/resources/vulcan/components/model/model_kinds.md#materialization-strategy_1)
* [INCREMENTAL\_BY\_PARTITION](/concepts/resources/vulcan/components/model/model_kinds.md#materialization-strategy_3)
* [FULL](/concepts/resources/vulcan/components/model/model_kinds.md#materialization-strategy_2)

{% hint style="info" %}
The `BigQuery Data Editor` and `BigQuery Job User` roles together provide the minimum permissions required for Vulcan to operate.
{% endhint %}

{% hint style="warning" %}
Never commit your keyfile to version control. Add it to `.gitignore` and store it securely.
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://v2.dataos.info/concepts/resources/vulcan/configurations/engines/bigquery.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.