Google Cloud Pub\Sub and PostgreSQL Integration

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Capture Google Cloud Pub\Sub messages and store them reliably in PostgreSQL for analysis and reporting. Latenode simplifies this with a visual editor and affordable execution-based pricing. Enhance data pipelines by integrating custom JavaScript logic for sophisticated transformations.

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Google Cloud Pub\Sub

PostgreSQL

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud Pub\Sub and PostgreSQL

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

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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.

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Add the PostgreSQL Node

Next, click the plus (+) icon on the Google Cloud Pub\Sub node, select PostgreSQL from the list of available apps, and choose the action you need from the list of nodes within PostgreSQL.

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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.

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Configure the Google Cloud Pub\Sub 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.

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Set Up the Google Cloud Pub\Sub 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.
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Save and Activate the Scenario

After configuring Google Cloud Pub\Sub, 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 Pub\Sub and PostgreSQL integration works as expected. Depending on your setup, data should flow between Google Cloud Pub\Sub 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 Pub\Sub and PostgreSQL

Google Cloud Pub/Sub + PostgreSQL + Slack: When a new message is received in Google Cloud Pub/Sub, the message data is logged into a PostgreSQL database. A Slack notification is then sent to a specified channel to inform the team about the new message.

PostgreSQL + Google Cloud Storage + Google Cloud Pub/Sub: When a new or updated row is detected in a PostgreSQL database, a backup of the change is uploaded to Google Cloud Storage. A message is then published to Google Cloud Pub/Sub to notify subscribers of the data archival.

Google Cloud Pub\Sub and PostgreSQL integration alternatives

About Google Cloud Pub\Sub

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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.

See how Latenode works

FAQ Google Cloud Pub\Sub and PostgreSQL

How can I connect my Google Cloud Pub\Sub account to PostgreSQL using Latenode?

To connect your Google Cloud Pub\Sub account to PostgreSQL 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 PostgreSQL accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I archive Pub\Sub messages to PostgreSQL?

Yes, you can archive messages using Latenode. Automatically store historical data for auditing, reporting, and analysis. Leverage Latenode's no-code blocks and JavaScript functions.

What types of tasks can I perform by integrating Google Cloud Pub\Sub with PostgreSQL?

Integrating Google Cloud Pub\Sub with PostgreSQL allows you to perform various tasks, including:

  • Synchronizing real-time Pub\Sub data into PostgreSQL tables.
  • Triggering database updates based on Pub\Sub message content.
  • Archiving Pub\Sub messages in PostgreSQL for compliance.
  • Creating real-time dashboards using Pub\Sub data in PostgreSQL.
  • Building event-driven applications powered by both services.

How do I transform Pub\Sub messages before loading into PostgreSQL?

Use Latenode's built-in data transformation blocks or JavaScript steps to format Pub\Sub data before it's stored in PostgreSQL.

Are there any limitations to the Google Cloud Pub\Sub and PostgreSQL integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Complex data transformations may require JavaScript coding.
  • Large-volume data transfers can be subject to API rate limits.
  • Maintaining data consistency requires careful workflow design.

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