Connect Cuttly and TimescaleDB to Build Intelligent Automations

Choose a Trigger

Cuttly

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 Cuttly and TimescaleDB?

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

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

Absolutely. You can customize how Cuttly 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 Cuttly and TimescaleDB?

The data sync between Cuttly 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 Cuttly 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 Cuttly and TimescaleDB?

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

Cuttly

About Cuttly

Cutt.ly is a URL shortener with advanced links tracking & API. Link Management Platform. Simplify, track & manage your links like a pro.

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