Connect Freshdesk and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Ticket
New Contact
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Freshdesk and TimescaleDB
Enable Integrations or automations with these events of Freshdesk and TimescaleDB
Triggers
New Ticket
Trigger when a new ticket created.
New Contact
Trigger when a new contect is cteated.
Actions
Create a Contact
Creates a new contact
Create a Company
Creates a new company
Create Forum Category
Create a new forum category
Create a Forum
Creates a new forum.
Create a Forum Topic
Creates a new forum topic
Add Notes to a Tickets
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Frequently Asked Questions
To start, connect both your Freshdesk and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Freshdesk triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Freshdesk 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 Freshdesk 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 Freshdesk 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 Freshdesk
Freshdesk is a cloud-based customer service software that provides helpdesk support with all smart automations to get things done faster. It offers ticketing, automation, reporting, and collaboration features to streamline support processes and improve customer engagement.
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
