
When this happens...
New Registrant
Registrant Attended
Registrant Didn't Attend
Registrant Watched Reply
Session Created
Session Started
Session Ended
New Event
Event Published
Job Ended

Automatically do this!
Enable Integrations or automations with these events of Livestorm and TimescaleDB
Triggers when a new participant register for an Event
Triggers when a registrant attended an Event Session that just ended
Triggers when a registrant didn't attend an Event Session that just ended
Triggers when a registrant has watched an replay of an Event Session
Triggers when a session is created
Triggers when an Event Session starts
Create an Event Session
Deletes a Session
Remove someone from a session
Delete an event
Partially Update an Event
Partially update a session
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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your Livestorm and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Livestorm triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Livestorm 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 Livestorm 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 Livestorm 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.
Livestorm is an end-to-end engagement platform that enables you to connect, engage, and capture actionable insights in one place.
Learn MoreTimescaleDB 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