Connect Eledo and TimescaleDB to Build Intelligent Automations

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Eledo

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TimescaleDB

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Enable Integrations or automations with these events of Eledo and TimescaleDB

Enable Integrations or automations with these events of Eledo and TimescaleDB

Actions

Generate Document

Generate Document

Create a PDF from a selected Eledo template using provided JSON data and return a download link. Optionally mark the file as temporary for one-time download.

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Frequently Asked Questions

How do I start an integration between Eledo and TimescaleDB?

To start, connect both your Eledo and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Eledo triggers actions in TimescaleDB (or vice versa).

Can we customize how data from Eledo is recorded in TimescaleDB?

Absolutely. You can customize how Eledo data is recorded in TimescaleDB. This includes choosing which data fields go into which fields of TimescaleDB, setting up custom formats, and filtering out unwanted information.

How often does the data sync between Eledo and TimescaleDB?

The data sync between Eledo and TimescaleDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from Eledo to TimescaleDB?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Eledo and TimescaleDB?

Yes, you can set conditional logic to control the flow of data between Eledo and TimescaleDB. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.

Eledo

About Eledo

Eledo is a PDF service that helps you with your automated document creation. Build your document template in Eledo online editor and include dynamic elements.

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TimescaleDB

About TimescaleDB

TimescaleDB is a powerful time-series database designed for fast ingest and complex queries, making it ideal for handling time-series data efficiently. It extends PostgreSQL, providing scalability and performance enhancements specifically for time-series workloads.

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