Connect Shippo and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Order
New Shipping Label
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Shippo and TimescaleDB
Enable Integrations or automations with these events of Shippo and TimescaleDB
Triggers
New Order
Triggers when a new order is created in Shippo.
New Shipping Label
Trigger when a new shipping label is created.
Actions
Search Orders
Get a list of orders that match your filters, such as status, date range, or store.
Create Shipping Order
Creates a new shipping order in Shippo.
Find Shipping Label
Gets a shipping label by label ID or by searching with filters.
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Frequently Asked Questions
To start, connect both your Shippo and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Shippo triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Shippo 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 Shippo 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 Shippo 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 Shippo
Shippo's API standardizes carrier processes and streamlines the complexities of shipping, so you can offer a best-in-class solution without the upkeep.
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
