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

Add the Postmark Node
Select the Postmark node from the app selection panel on the right.


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


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Authenticate Google Cloud BigQuery (REST)
Now, click the Google Cloud BigQuery (REST) 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 (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.
Configure the Postmark and Google Cloud BigQuery (REST) 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 Postmark and Google Cloud BigQuery (REST) 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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Save and Activate the Scenario
After configuring Postmark, Google Cloud BigQuery (REST), 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 Postmark and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Postmark and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Postmark and Google Cloud BigQuery (REST)
Postmark + Google Cloud BigQuery (REST) + Slack: When a new email bounce is detected in Postmark, the bounce data is inserted into a Google Cloud BigQuery table for analysis. If the number of bounces exceeds a certain threshold within a defined period (requiring a query job in BigQuery), a notification is sent to a designated Slack channel to alert the team.
Google Cloud BigQuery (REST) + Postmark + Google Sheets: A query is run in Google Cloud BigQuery to analyze email campaign data. Based on the results of the query (e.g., users who haven't opened an email), personalized emails are sent via Postmark. The results of these email sends (opens, bounces) are logged in Google Sheets for tracking and reporting.
Postmark and Google Cloud BigQuery (REST) integration alternatives

About Postmark
Use Postmark in Latenode to automate transactional emails. Connect events from your apps to trigger personalized messages, like order confirmations or password resets. Benefit from Postmark’s deliverability, plus Latenode's visual workflow builder and flexible logic to filter events and enrich email data, ensuring accurate and timely communication.
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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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FAQ Postmark and Google Cloud BigQuery (REST)
How can I connect my Postmark account to Google Cloud BigQuery (REST) using Latenode?
To connect your Postmark account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Postmark and click on "Connect".
- Authenticate your Postmark and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze email delivery data using Postmark and Google Cloud BigQuery (REST)?
Yes, with Latenode! Automate data transfer to BigQuery, then use its powerful analytics. Gain deeper insights into email performance and optimize your campaigns.
What types of tasks can I perform by integrating Postmark with Google Cloud BigQuery (REST)?
Integrating Postmark with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automatically backing up all Postmark email event data to BigQuery.
- Creating custom dashboards to visualize email performance metrics.
- Analyzing trends in email opens, clicks, and bounces over time.
- Enriching email data in BigQuery with other customer data sources.
- Triggering automated alerts based on email delivery failures.
Can I filter Postmark data before sending it to Google Cloud BigQuery (REST)?
Yes! Latenode's data transformation tools let you filter and transform Postmark data before loading it into Google Cloud BigQuery (REST), ensuring data quality.
Are there any limitations to the Postmark and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data loading from Postmark to Google Cloud BigQuery (REST) might take time.
- Complex data transformations may require custom JavaScript code.
- BigQuery costs can increase with large volumes of email data.