Connect Agora and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Agora
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Agora and TimescaleDB
Enable Integrations or automations with these events of Agora and TimescaleDB
Actions
Get project usage
Gets the usage data of a specified project.
Enable or Disable Primary app
Enables or disables the primary app certificate for a project by ID.
Set IP Address
Sets the IP of the recording server for a project by ID.
Enable or Disable a Project
Enables or Disables a project by ID.
Get a Project by ID
Gets the info on a project by ID.
Create a project
Creates a new project.
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Frequently Asked Questions
To start, connect both your Agora and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Agora triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Agora 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 Agora 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 Agora 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 Agora
Agora offers real-time voice, video, and live interactive streaming platforms, enabling developers to embed real-time video and voice functionalities into their applications.
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
