IntegrationsWizy ChatTimescaleDB
Wizy Chat + TimescaleDB

Connect Wizy Chat and TimescaleDB to Build Intelligent Automations

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Wizy Chat

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TimescaleDB

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Frequently Asked Questions

How do I start an integration between Wizy Chat and TimescaleDB?

To start, connect both your Wizy Chat and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Wizy Chat triggers actions in TimescaleDB (or vice versa).

Can we customize how data from Wizy Chat is recorded in TimescaleDB?

Absolutely. You can customize how Wizy Chat 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.

How often does the data sync between Wizy Chat and TimescaleDB?

The data sync between Wizy Chat and TimescaleDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from Wizy Chat to TimescaleDB?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Wizy Chat and TimescaleDB?

Yes, you can set conditional logic to control the flow of data between Wizy Chat 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.

Wizy Chat

About Wizy Chat

Wizy Chat is a versatile communication platform designed to enhance team collaboration and streamline communication processes. It offers a range of features including instant messaging, file sharing, and integration with other productivity tools, making it an ideal solution for businesses looking to improve internal communication and team efficiency.

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TimescaleDB

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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