IntegrationsUservoiceTimescaleDB
Uservoice + TimescaleDB

Connect Uservoice and TimescaleDB to Build Intelligent Automations

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Uservoice

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TimescaleDB

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Frequently Asked Questions

How do I start an integration between Uservoice and TimescaleDB?

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

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

Absolutely. You can customize how Uservoice 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 Uservoice and TimescaleDB?

The data sync between Uservoice 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 Uservoice 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 Uservoice and TimescaleDB?

Yes, you can set conditional logic to control the flow of data between Uservoice 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.

Uservoice

About Uservoice

Uservoice is a platform designed to help businesses gather and prioritize customer feedback, manage support tickets, and improve customer satisfaction. It provides tools for capturing user suggestions, voting on ideas, and tracking the progress of feature requests.

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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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