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

# BigQuery

> Learn how to configure Google BigQuery as a destination in Artie, including project setup, dataset configuration, service account credentials, and query priority settings.

## Required settings

* Project identifier
* Dataset
* Service account

<Accordion title="Find project identifier">
  Go into your [BigQuery console](https://console.cloud.google.com/bigquery) and the project ID is at the top of the navigation bar.

  <img src="https://mintcdn.com/artie/cR74rDu7gj_LCvTI/assets/gcp_project_id.png?fit=max&auto=format&n=cR74rDu7gj_LCvTI&q=85&s=7cc0d9773b67436284407be75b09eaaf" alt="GCP project id" width="548" height="362" data-path="assets/gcp_project_id.png" />
</Accordion>

<Accordion title="Find dataset name">
  To find this out, go to [BigQuery console](https://console.cloud.google.com/bigquery), and you will see the dataset name on the left side of the screen.

  <img src="https://mintcdn.com/artie/cR74rDu7gj_LCvTI/assets/bigquery_dataset.png?fit=max&auto=format&n=cR74rDu7gj_LCvTI&q=85&s=8eb5a187cda34ed692db72c1c3d1de07" alt="BigQuery dataset" width="695" height="644" data-path="assets/bigquery_dataset.png" />
</Accordion>

<Accordion title="Retrieving your credentials">
  To create a service account, please do the following:

  1. Go to the `IAM & Admin` section in your GCP console and click `Service Accounts`.
  2. Click on `Create Service Account`, give it a name and click `Create and Continue`.
  3. Grant the `BigQuery Admin` role to the service account click `Done`.
  4. Go into the service account you just created and click on `Keys` and then `Add Key`.
  5. Choose `JSON` and click `Create`. This will download a JSON file with your credentials.
</Accordion>

## Queue priority

BigQuery supports two query priority modes that determine how your queries are scheduled and executed.

| Mode            | Description                                                                                                                                                      |
| --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **INTERACTIVE** | Queries are executed as soon as possible and count against BigQuery's concurrent query limits. Best for time-sensitive operations where low latency is critical. |
| **BATCH**       | Queries are queued and executed when resources become available. Does not count against concurrent query limits. Best for large, non-urgent workloads.           |

<Note>
  By default, Artie uses **INTERACTIVE** priority.
</Note>

### Pricing model considerations

The impact of queue priority depends on your BigQuery pricing model:

<Tabs>
  <Tab title="On-demand">
    With on-demand pricing, you pay per byte scanned regardless of priority mode. The key differences are:

    * **INTERACTIVE** counts against your project's concurrent query limit (default: 100 queries)
    * **BATCH** does not count against concurrent limits, avoiding potential throttling during high-throughput periods

    **Recommendation**: Consider using BATCH for CDC workloads to avoid hitting concurrency limits during peak replication.
  </Tab>

  <Tab title="Capacity slots">
    With capacity slots (BigQuery Editions), you pay for reserved compute capacity. The key differences are:

    * **INTERACTIVE** queries get prioritized access to your allocated slots
    * **BATCH** queries only run when slots are available after INTERACTIVE queries are served

    **Recommendation**: Use INTERACTIVE since you're paying for dedicated slots and want your CDC queries to run immediately rather than wait behind other workloads.
  </Tab>
</Tabs>

### Best practices

* Consider [partitioning](/guides/database/bigquery/enable-bigquery-partitioning) your large tables to improve merge performance and reduce costs.
* Review the [capacity pricing guide](/guides/database/bigquery/capacity-pricing) to understand BigQuery's pricing models and avoid unexpected bills.