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

Add the Google Cloud Text-To-Speech Node
Select the Google Cloud Text-To-Speech node from the app selection panel on the right.


Google Cloud Text-To-Speech

Configure the Google Cloud Text-To-Speech
Click on the Google Cloud Text-To-Speech node to configure it. You can modify the Google Cloud Text-To-Speech 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 Text-To-Speech node, select PostgreSQL from the list of available apps, and choose the action you need from the list of nodes within PostgreSQL.


Google Cloud Text-To-Speech
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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 Text-To-Speech 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 Text-To-Speech 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 Text-To-Speech
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Iterator
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Webhook response


Save and Activate the Scenario
After configuring Google Cloud Text-To-Speech, 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 Text-To-Speech and PostgreSQL integration works as expected. Depending on your setup, data should flow between Google Cloud Text-To-Speech 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 Text-To-Speech and PostgreSQL
PostgreSQL + Google Cloud Text-To-Speech + Slack: When a new or updated row is added to a PostgreSQL database, its content is converted into an audio message using Google Cloud Text-To-Speech and sent to a designated Slack channel.
PostgreSQL + Google Cloud Text-To-Speech + Email: Executes a SQL query in PostgreSQL, converts the resulting data into an audio summary via Google Cloud Text-To-Speech, and delivers this audio report to specified email addresses.
Google Cloud Text-To-Speech and PostgreSQL integration alternatives

About Google Cloud Text-To-Speech
Use Google Cloud Text-To-Speech in Latenode to automate voice notifications, generate audio content from text, and create dynamic IVR systems. Integrate it into any workflow with a drag-and-drop interface. No code is required, and it's fully customizable with JavaScript for complex text manipulations. Automate voice tasks efficiently without vendor lock-in.
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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 Text-To-Speech and PostgreSQL
How can I connect my Google Cloud Text-To-Speech account to PostgreSQL using Latenode?
To connect your Google Cloud Text-To-Speech account to PostgreSQL on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Text-To-Speech and click on "Connect".
- Authenticate your Google Cloud Text-To-Speech and PostgreSQL accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I archive synthesized speech data in PostgreSQL?
Yes, you can easily archive synthesized speech data using Latenode. This allows for organized data storage and efficient retrieval for analysis or future use, all automated.
What types of tasks can I perform by integrating Google Cloud Text-To-Speech with PostgreSQL?
Integrating Google Cloud Text-To-Speech with PostgreSQL allows you to perform various tasks, including:
- Store synthesized audio files metadata in a structured database.
- Log text inputs and corresponding audio output paths.
- Create a searchable archive of all generated speech data.
- Trigger speech synthesis based on database updates.
- Manage and track voice-based notifications and alerts.
Can I use custom voices with Google Cloud Text-To-Speech on Latenode?
Yes, Latenode supports custom voices. Leverage advanced logic, JavaScript, and prompt-based AI blocks to create truly unique voice experiences.
Are there any limitations to the Google Cloud Text-To-Speech and PostgreSQL integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits of the Google Cloud Text-To-Speech API apply.
- Large audio file storage may impact PostgreSQL performance.
- Complex workflow logic requires JavaScript or AI block knowledge.