Connect Dribbble and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Project Added
New Shot Added
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Dribbble and TimescaleDB
Enable Integrations or automations with these events of Dribbble and TimescaleDB
Triggers
New Project Added
Runs when new project is added
New Shot Added
Runs when new shot is added
Actions
Update Shot
Edit shot details
Delete Shot
Remove a shot from account
List My Shots
List all shots in your account
Get User Profile
Show your profile
Get Shot
Get details for a single shot by ID.
Create Project
Create a Dribbble project
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Frequently Asked Questions
To start, connect both your Dribbble and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Dribbble triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Dribbble 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 Dribbble 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 Dribbble 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 Dribbble
Discover and connect with designers worldwide, showcase creative work, and get inspired.
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
