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

Add the Google Cloud Firestore Node
Select the Google Cloud Firestore node from the app selection panel on the right.

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

Google Cloud Firestore
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PostgreSQL

Authenticate PostgreSQL
Now, click the PostgreSQL node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your PostgreSQL settings. Authentication allows you to use PostgreSQL through Latenode.
Configure the Google Cloud Firestore and PostgreSQL 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 Firestore and PostgreSQL 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.

JavaScript
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AI Anthropic Claude 3
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PostgreSQL
Trigger on Webhook
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Google Cloud Firestore
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud Firestore, PostgreSQL, 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 Firestore and PostgreSQL integration works as expected. Depending on your setup, data should flow between Google Cloud Firestore and PostgreSQL (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 Firestore and PostgreSQL
Google Cloud Firestore + PostgreSQL + Google Sheets: When a document is updated in Google Cloud Firestore, the changes are mirrored to a PostgreSQL database, and then a log entry is added to a Google Sheet.
PostgreSQL + Google Cloud Firestore + Slack: When a row is updated in a PostgreSQL database, the changes are mirrored to a document in Google Cloud Firestore, and a Slack message is sent to a designated channel to notify the team about the update.
Google Cloud Firestore and PostgreSQL integration alternatives
About Google Cloud Firestore
Use Google Cloud Firestore in Latenode to build real-time data workflows. Automate database tasks like data synchronization, backups, or event-driven updates without coding. Combine Firestore with AI tools and webhooks for powerful apps. Create complex workflows with simple visual tools and scale affordably with Latenode's pay-as-you-go pricing.
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About PostgreSQL
Use PostgreSQL in Latenode to automate database tasks. Build flows that react to database changes or use stored data to trigger actions in other apps. Automate reporting, data backups, or sync data across systems without code. Scale complex data workflows easily within Latenode's visual editor.
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FAQ Google Cloud Firestore and PostgreSQL
How can I connect my Google Cloud Firestore account to PostgreSQL using Latenode?
To connect your Google Cloud Firestore account to PostgreSQL on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Firestore and click on "Connect".
- Authenticate your Google Cloud Firestore and PostgreSQL accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I sync Firestore data to PostgreSQL for reporting?
Yes, you can! Latenode's visual editor simplifies data synchronization, letting you easily create reporting dashboards from your Firestore data stored in PostgreSQL.
What types of tasks can I perform by integrating Google Cloud Firestore with PostgreSQL?
Integrating Google Cloud Firestore with PostgreSQL allows you to perform various tasks, including:
- Backing up Google Cloud Firestore data to a PostgreSQL database.
- Migrating data from Google Cloud Firestore to PostgreSQL for analysis.
- Synchronizing user data between Google Cloud Firestore and PostgreSQL.
- Creating real-time dashboards using data from both platforms.
- Triggering PostgreSQL actions based on Google Cloud Firestore events.
Can I use JavaScript code to transform data between Firestore and PostgreSQL?
Yes! Latenode allows you to use JavaScript blocks to manipulate data, ensuring seamless transformations between Google Cloud Firestore and PostgreSQL.
Are there any limitations to the Google Cloud Firestore and PostgreSQL integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations may require custom JavaScript code.
- Large data migrations can be resource-intensive and time-consuming.
- The integration relies on the availability and performance of both services.