How to connect Google Cloud BigQuery (REST) and Google Cloud Storage
Create a New Scenario to Connect Google Cloud BigQuery (REST) and Google Cloud Storage
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery (REST), triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery (REST) or Google Cloud Storage will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Google Cloud Storage, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery (REST) Node
Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.

Google Cloud BigQuery (REST)
Configure the Google Cloud BigQuery (REST)
Click on the Google Cloud BigQuery (REST) node to configure it. You can modify the Google Cloud BigQuery (REST) URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud Storage Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select Google Cloud Storage from the list of available apps, and choose the action you need from the list of nodes within Google Cloud Storage.

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Google Cloud Storage

Authenticate Google Cloud Storage
Now, click the Google Cloud Storage node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud Storage settings. Authentication allows you to use Google Cloud Storage through Latenode.
Configure the Google Cloud BigQuery (REST) and Google Cloud Storage Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud BigQuery (REST) and Google Cloud Storage Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Google Cloud Storage
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Google Cloud Storage, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery (REST) and Google Cloud Storage integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Google Cloud Storage (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud BigQuery (REST) and Google Cloud Storage
Google Cloud BigQuery (REST) + Google Cloud Storage + Google Sheets: Analyze data in BigQuery using a query. The results of the query are then stored as a CSV file in Google Cloud Storage. Finally, the data from the CSV file is added to a Google Sheet.
Google Cloud Storage + Google Cloud BigQuery (REST) + Slack: When a new file is uploaded to Google Cloud Storage, it triggers a BigQuery job to load the data from the file into a BigQuery table. Upon successful data load, a message is sent to a designated Slack channel, notifying analysts of the new data.
Google Cloud BigQuery (REST) and Google Cloud Storage integration alternatives
About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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About Google Cloud Storage
Use Google Cloud Storage in Latenode for automated file management. Upload, download, and manage files in your workflows. Automate backups, data archiving, or image processing. Connect GCS to other apps for seamless data transfer and triggering events. Latenode's visual editor simplifies complex file-based automations.
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FAQ Google Cloud BigQuery (REST) and Google Cloud Storage
How can I connect my Google Cloud BigQuery (REST) account to Google Cloud Storage using Latenode?
To connect your Google Cloud BigQuery (REST) account to Google Cloud Storage on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and Google Cloud Storage accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I archive BigQuery data to cold storage automatically?
Yes, you can! Latenode automates the process, moving data based on triggers or schedules. This ensures cost-effective storage and efficient data management.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Google Cloud Storage?
Integrating Google Cloud BigQuery (REST) with Google Cloud Storage allows you to perform various tasks, including:
- Backup BigQuery datasets to Google Cloud Storage for disaster recovery.
- Automate data archiving from BigQuery to lower-cost storage tiers.
- Load data from Google Cloud Storage into BigQuery for analysis.
- Transform data in BigQuery and store the results in Google Cloud Storage.
- Create automated data pipelines for ETL processes using both services.
What credentials do I need to connect BigQuery to Latenode?
You'll need a Google Cloud service account with the necessary permissions and its JSON key file to securely authenticate your BigQuery account.
Are there any limitations to the Google Cloud BigQuery (REST) and Google Cloud Storage integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers may be subject to Google Cloud's API rate limits.
- Complex data transformations might require custom JavaScript code.
- Real-time synchronization may experience delays due to API polling intervals.