Connect ProductPlan and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Bar Appears on Roadmap
Roadmap Is Updated
Roadmap Bar Is Updated
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of ProductPlan and TimescaleDB
Enable Integrations or automations with these events of ProductPlan and TimescaleDB
Triggers
New Bar Appears on Roadmap
Runs when New Bar Appears on Roadmap
Roadmap Is Updated
Runs when roadmap is updated
Roadmap Bar Is Updated
Runs when roadmap bar is updated
Actions
Create New Bar
Add a new bar to your roadmap.
Get Roadmap Bars
Get all bars for a roadmap.
Update Bar
Update a roadmap bar by ID.
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Frequently Asked Questions
To start, connect both your ProductPlan and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in ProductPlan triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how ProductPlan 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 ProductPlan 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 ProductPlan 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 ProductPlan
Integrate with ProductPlan to streamline your product roadmap planning and visualization. Automate updates, share roadmaps, and synchronize data across your product management tools.
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
