BigQuery

Connect to Google BigQuery to run SQL queries against your datasets and write rows to tables from your AI workflows.

Connectors

Choose the connector that matches your authentication method. The options below use the names shown in StackAI.

Connector	Authentication
BigQuery	Credentials

BigQuery

Connect to BigQuery to analyze and manage large volumes of data. Supports SQL queries and data operations across multiple clouds.

Set up in BigQuery

1. In Google Cloud, enable BigQuery for the project that will run the queries.

2. Create or select a service account. Grant permission to run BigQuery jobs in that project and access the required datasets.

3. Create a JSON key for the service account and retain the complete downloaded document for StackAI.

Set up in StackAI

1. Open Settings → Connections, add a connection, and select BigQuery.

2. Enter the credentials and connection details in the fields below.

3. Save the connection and check its connection status. Select this saved connection when configuring an action or feature that uses it.

Connection fields

StackAI field	Required	What to enter
Project ID	Yes	The Google Cloud project ID where your BigQuery datasets are located.
Credentials JSON	Yes	JSON key for a service account scoped to read-only BigQuery access. Grant only roles/bigquery.dataViewer on the target datasets and roles/bigquery.jobUser on the project — do NOT grant dataEditor/dataOwner or admin roles.

Provider documentation: Setup reference 1, Setup reference 2.

Verify the connection

Check that the connection is healthy. Then run a read operation against a resource the connected account can access. A successful connection check confirms authentication; it does not guarantee permission for every action.

If access is denied, check the credential or OAuth permissions, the selected account or environment, and access to the specific resource. Update expired credentials or reconnect after permissions change.

Detailed setup guides

• Connect BigQuery

Use an action

1. Add the required BigQuery action to the workflow.

2. Select a connection when the action requests one.

3. Complete the required fields. Use the reference picker when a value comes from another workflow step.

4. Run the workflow and inspect the action’s output. Check the result before using it in a later step.

Actions

Query BigQuery

Query a Google BigQuery database with a plain english query or a SQL query

Inputs

Field	Type	Required	Description
Schema	string	No	Database schema with tables, columns, and types (BigQuery format).
Dataset	string	No	The dataset to query. If not provided, the default dataset will be used.
Query	string	Yes	Enter your query in plain English or SQL format to execute against the database. Default: .

Outputs

Field	Type	Description
Query	string	The SQL query that was executed.
Results	string	The results of the query.
Truncated	boolean	True if the result set was truncated by the row cap.

Write to BigQuery

Write a row to a Google BigQuery table from JSON data

Inputs

Field	Type	Required	Description
Table	select (string)	Yes	The BigQuery table to write data to. Options load from the selected connection.
Data	string	Yes	The JSON data to write as a row to BigQuery. Default: .
Insert Mode	select (string)	No	The mode for inserting data (INSERT or INSERT_IGNORE). Available values: Insert, Insert and Ignore Errors. Default: INSERT.

Outputs

Field	Type	Description
Success	boolean	Whether the write operation was successful.
Message	string	Success or error message from the write operation.
Errors	string_array	List of errors if any occurred during the write operation.

Important behavior

Actions that create, update, send, or delete data can change the connected service. Review their inputs before running them. A retry can repeat an operation; consider this when configuring retries for actions that change data.

The catalog lists the fields and capabilities available in the supplied provider definition. Availability can also depend on your deployment and organization’s Feature Access settings.