Connect SerwerSMS and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Message Received
New Message Sent
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of SerwerSMS and TimescaleDB
Enable Integrations or automations with these events of SerwerSMS and TimescaleDB
Triggers
New Message Received
Triggers when a new message is received.
New Message Sent
Triggers when a new message is sent.
Actions
Add Phone Number to Blacklist
Add a phone number to the blacklist to prevent it from receiving SMS.
Add Contact
Add a new contact.
Send SMS
Send message SMS.
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Frequently Asked Questions
To start, connect both your SerwerSMS and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in SerwerSMS triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how SerwerSMS 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 SerwerSMS 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 SerwerSMS 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 SerwerSMS
SerwerSMS is a comprehensive platform for managing SMS communication, offering tools for sending bulk messages, notifications, and marketing campaigns. It is designed to enhance customer engagement and streamline communication 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
