Connect Dovetail and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Project
New Insight
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Dovetail and TimescaleDB
Enable Integrations or automations with these events of Dovetail and TimescaleDB
Triggers
New Project
Triggers when a new project is created
New Insight
Actions
Create Note
Create Data Point
Add Data to Project
Add Data to Project.
List Tags
List of all tags associated with a workspace
List Insights
List of insights associated with a workspace.
List Contacts
List of contacts within a workspace.
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Frequently Asked Questions
To start, connect both your Dovetail and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Dovetail triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Dovetail 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 Dovetail 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 Dovetail 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 Dovetail
Dovetail lets you organize user research data, analyze it together, and share insights with your team. Understand your customers with Dovetail and build better things.
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
