Connect Bexio and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Order
New Quote
New Sales-Invoice
New/Updated Company
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Bexio and TimescaleDB
Enable Integrations or automations with these events of Bexio and TimescaleDB
Triggers
New Order
Triggers when a new order is created
New Quote
Triggers when a new quote is created or updated
New Sales-Invoice
Triggers when a new sales invoice is created or updated
New/Updated Company
Triggers when a company is added or updated
Actions
Create Product
Creates a product
Create Project
Creates a Project
Create Person
Creates a person
Create Company
Creates a company
Export Invoice to PDF
Exports an existing sales invoice as a pdf document
Search Project
Search a project
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Frequently Asked Questions
To start, connect both your Bexio and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Bexio triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Bexio 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 Bexio 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 Bexio 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 Bexio
Bexio is a business platform for offering accounting, invoices, payroll, and more for small companies in Switzerland.
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.
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