Captions and PostgreSQL Integration

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Automatically archive transcripts from Captions to PostgreSQL for secure storage and analysis. Latenode’s visual editor makes this complex data workflow simple. Plus, scale affordably by paying only for execution time.

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Captions

PostgreSQL

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Captions and PostgreSQL

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

Add the Captions Node

Select the Captions node from the app selection panel on the right.

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Configure the Captions

Click on the Captions node to configure it. You can modify the Captions URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the PostgreSQL Node

Next, click the plus (+) icon on the Captions 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 Captions 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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Run node once

Set Up the Captions 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 Captions, 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 Captions and PostgreSQL integration works as expected. Depending on your setup, data should flow between Captions 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 Captions and PostgreSQL

Captions + PostgreSQL + Slack: When a video generation request is submitted in Captions, the request details are stored in a PostgreSQL database. Upon completion, a message is sent to a designated Slack channel notifying the team.

PostgreSQL + Captions + Google Sheets: When a new or updated row is added to the PostgreSQL database (presumably related to caption performance), relevant data is retrieved and updated in a Google Sheets spreadsheet to track caption performance metrics.

Captions and PostgreSQL integration alternatives

About Captions

Need accurate, automated captions for videos? Integrate Captions with Latenode to generate and sync subtitles across platforms. Automate video accessibility for marketing, training, or support. Latenode adds scheduling, file handling, and error control to Captions, making scalable captioning workflows simple and efficient.

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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 Captions and PostgreSQL

How can I connect my Captions account to PostgreSQL using Latenode?

To connect your Captions account to PostgreSQL on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Captions and click on "Connect".
  • Authenticate your Captions and PostgreSQL accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I archive Captions transcripts to PostgreSQL automatically?

Yes, you can! Latenode allows you to automatically archive Captions transcripts to PostgreSQL. This ensures secure backups and enables advanced data analysis within your database.

What types of tasks can I perform by integrating Captions with PostgreSQL?

Integrating Captions with PostgreSQL allows you to perform various tasks, including:

  • Storing Captions video transcripts directly into a PostgreSQL database.
  • Automatically updating PostgreSQL records with new Captions transcription data.
  • Triggering workflows based on specific keywords found in Captions transcripts.
  • Creating data visualizations from Captions transcript data stored in PostgreSQL.
  • Backing up Captions data securely by archiving it to a PostgreSQL instance.

What Captions data can I access in Latenode?

Latenode allows you to access Captions transcript text, timestamps, speaker labels, and confidence scores for use in your workflows.

Are there any limitations to the Captions and PostgreSQL integration on Latenode?

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

  • Large transcript files may experience processing delays.
  • Real-time data synchronization is not supported.
  • Complex data transformations may require JavaScript coding.

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