Connect Flow and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Task
Task Completed
New Project
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Flow and TimescaleDB
Enable Integrations or automations with these events of Flow and TimescaleDB
Triggers
New Task
Triggers when a new task is created in GetFlow.
Task Completed
Triggers when a task is marked as completed in GetFlow.
New Project
Triggers when a new project is added.
Actions
Create Task
Creates a new task in GetFlow Account.
list task
get a task in flow.
Get List
get a List in flow.
List workspaces
get a workspaces in flow.
List memberships
get a memberships in flow.
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Frequently Asked Questions
To start, connect both your Flow and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Flow triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Flow 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 Flow 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 Flow 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 Flow
GetFlow is a task and project management tool designed to help teams collaborate efficiently and manage their workflows effectively. It offers features such as task assignments, due dates, project timelines, and team communication to streamline project management processes.
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
