Connect HigherGov and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for HigherGov
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of HigherGov and TimescaleDB
Enable Integrations or automations with these events of HigherGov and TimescaleDB
Actions
List All Agencies
Get a list of agencies.
List All People
Get a list of People.
List Vehicles
Get a list of vehicles.
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Frequently Asked Questions
To start, connect both your HigherGov and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in HigherGov triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how HigherGov 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 HigherGov 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 HigherGov 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 HigherGov
HigherGov is a comprehensive platform designed to streamline and enhance government operations and public sector management. It offers tools and solutions for efficient governance, policy implementation, and public service delivery, ensuring transparency and accountability in government processes.
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
