Connect robolytix and TimescaleDB to Build Intelligent Automations

Choose a Trigger

robolytix

When this happens...

Choose an Action

TimescaleDB

Automatically do this!

We'll help you get started

Our team is all set to help you!

Customer support expert avatarTechnical support expert avatarAutomation specialist expert avatarIntegration expert avatar

Frequently Asked Questions

How do I start an integration between robolytix and TimescaleDB?

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

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

Absolutely. You can customize how robolytix 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 robolytix and TimescaleDB?

The data sync between robolytix 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 robolytix 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 robolytix and TimescaleDB?

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

robolytix

About robolytix

Robolytix is the key robot analytic tool for automated processes, providing all data you need for monitoring and managing software robots.

Learn More
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.

Learn More