Connect Cincopa and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Cincopa
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Cincopa and TimescaleDB
Enable Integrations or automations with these events of Cincopa and TimescaleDB
Actions
Create Gallery
Creates a Gallery.
Upload Asset to Gallery
Upload an asset to Gallery.
Delete Gallery
Deletes a gallery.
Set Gallery Metadata
This action allows you to update a gallery's metadata.
Add Gallery Assets
Adds Assets to Gallery.
Remove Galley Asset
Removes Asset from Galley.
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Frequently Asked Questions
To start, connect both your Cincopa and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Cincopa triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Cincopa 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.
The data sync between Cincopa and TimescaleDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Cincopa 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.
About Cincopa
Cincopa is multimedia solution allowing to handle all aspects of hosting, managing, publishing, and sharing multiple types of media content.
Learn MoreAbout 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
