Connect DitCal and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
Booking Cancelled
New Booking
Meeting Rescheduled
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of DitCal and TimescaleDB
Enable Integrations or automations with these events of DitCal and TimescaleDB
Triggers
Booking Cancelled
Triggers when a booking is cancelled.
New Booking
Triggers when a new booking is created.
Meeting Rescheduled
Triggers when meeting is rescheduled.
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Frequently Asked Questions
To start, connect both your DitCal and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in DitCal triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how DitCal 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 DitCal 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 DitCal 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 DitCal
DitCal is a comprehensive calendar and scheduling tool designed to streamline your personal and professional life. It offers features such as event scheduling, reminders, and integration with other productivity tools to ensure you never miss an important meeting or deadline.
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
