Connect TestDome and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Tests
New Candidates
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of TestDome and TimescaleDB
Enable Integrations or automations with these events of TestDome and TimescaleDB
Triggers
New Tests
Triggers when new tests are created.
New Candidates
Triggers when a new candidate is created.
Actions
Create Candidate
Creates a new candidate for specified test.
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Frequently Asked Questions
To start, connect both your TestDome and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in TestDome triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how TestDome 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 TestDome 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 TestDome 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 TestDome
TestDome offers automated skill testing solutions to help employers evaluate the capabilities of job candidates. It is widely used to screen before interviews and to assess skills accurately with a variety of programming, accounting, and office skill tests.
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
