Connect Agendor and TimescaleDB to Build Intelligent Automations
Enable Integrations or automations with these events of Agendor and TimescaleDB
Enable Integrations or automations with these events of Agendor and TimescaleDB
Triggers
New Activity
Triggers when new activity created.
Deal Won
Check whether the deal status has been updated to **Won**.
Update Deal
Triggers when deal is updated.
Update Organization
Check if an organization has been updated.
Update Person
Triggers when person is updated.
New Deal
Triggers when new deal is created.
Actions
Create Task for a Deal
Create a new task related to a deal
Create Task for an Organization
Create a new task related to an organization
Create Task for a Person
Create a new task related to a person.
Update a Deal
Update a deal by its id
Get a Deal
Get details of a deal by its id
Create Deal for an Organization
Create a new deal for an organization by org id.
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Frequently Asked Questions
To start, connect both your Agendor and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Agendor triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Agendor 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 Agendor 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 Agendor 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 Agendor
Customer relationship management platform where user can manage organizations, people, task and deals.
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About 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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