How to connect Google Cloud Pub\Sub and Google Cloud BigQuery
Create a New Scenario to Connect Google Cloud Pub\Sub and Google Cloud BigQuery
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 Pub\Sub, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud Pub\Sub or Google Cloud BigQuery will be your first step. To do this, click "Choose an app," find Google Cloud Pub\Sub or Google Cloud BigQuery, and select the appropriate trigger to start the scenario.

Add the Google Cloud Pub\Sub Node
Select the Google Cloud Pub\Sub node from the app selection panel on the right.


Google Cloud Pub\Sub

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


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Authenticate Google Cloud BigQuery
Now, click the Google Cloud BigQuery node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery settings. Authentication allows you to use Google Cloud BigQuery through Latenode.
Configure the Google Cloud Pub\Sub and Google Cloud BigQuery 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 Pub\Sub and Google Cloud BigQuery 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 BigQuery
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud Pub\Sub, Google Cloud BigQuery, 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 Pub\Sub and Google Cloud BigQuery integration works as expected. Depending on your setup, data should flow between Google Cloud Pub\Sub and Google Cloud BigQuery (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 Pub\Sub and Google Cloud BigQuery
Google Cloud Pub\Sub + Google Cloud BigQuery + Google Sheets: When a new message is received in Google Cloud Pub/Sub, it triggers a data analysis process in Google Cloud BigQuery. The results of this analysis are then visualized in a Google Sheet for easy interpretation and monitoring.
Google Cloud Pub\Sub + Google Cloud BigQuery + Slack: This automation monitors Google Cloud Pub/Sub messages, analyzes them for anomalies using Google Cloud BigQuery, and sends a notification to a designated Slack channel if any anomalies are detected, ensuring timely alerts for critical events.
Google Cloud Pub\Sub and Google Cloud BigQuery integration alternatives

About Google Cloud Pub\Sub
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About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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FAQ Google Cloud Pub\Sub and Google Cloud BigQuery
How can I connect my Google Cloud Pub\Sub account to Google Cloud BigQuery using Latenode?
To connect your Google Cloud Pub\Sub account to Google Cloud BigQuery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Pub\Sub and click on "Connect".
- Authenticate your Google Cloud Pub\Sub and Google Cloud BigQuery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I archive Pub/Sub messages into BigQuery?
Yes, you can archive Pub/Sub messages to BigQuery. Latenode simplifies the process, enabling automated data warehousing without coding. Analyze data, enhance reporting.
What types of tasks can I perform by integrating Google Cloud Pub\Sub with Google Cloud BigQuery?
Integrating Google Cloud Pub\Sub with Google Cloud BigQuery allows you to perform various tasks, including:
- Stream real-time Pub/Sub data into BigQuery for immediate analysis.
- Build automated data pipelines for event-driven data warehousing.
- Trigger BigQuery queries based on Pub/Sub message content.
- Create dashboards using data streamed from Pub/Sub via BigQuery.
- Implement data governance policies for your message streams.
Can I transform Pub/Sub messages before loading to BigQuery in Latenode?
Yes, Latenode offers built-in data transformation tools and JavaScript steps. This allows for flexible message manipulation before loading to BigQuery.
Are there any limitations to the Google Cloud Pub\Sub and Google Cloud BigQuery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations may require custom JavaScript code.
- BigQuery costs depend on data volume and query complexity.
- Initial setup requires correct permissions in both Google Cloud services.