Connect contractor plus and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
new lead is created
new client is added
new invoice is created
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of contractor plus and TimescaleDB
Enable Integrations or automations with these events of contractor plus and TimescaleDB
Triggers
new lead is created
runs when new lead is created
new client is added
runs when new client is added
new invoice is created
runs when new invoice is created
Actions
Create lead
Create a new lead to capture a potential client.
Create expense
Create an expense in Contractor+.
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Frequently Asked Questions
To start, connect both your contractor plus and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in contractor plus triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how contractor plus 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 contractor plus 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 contractor plus 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 contractor plus
Contractor+ facilitates contractors relationships with their Clients, REI’s & Property Managers. Scheduling, Estimating, Invoicing & more.
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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