Connect Mobile Message and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Inbound SMS Instant
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Mobile Message and TimescaleDB
Enable Integrations or automations with these events of Mobile Message and TimescaleDB
Triggers
New Inbound SMS Instant
Triggers when an inbound SMS is received.
Actions
Send SMS
Sends an SMS message.
Lookup Sent Messages
Get details of a sent message using message_id or custom_ref.
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Frequently Asked Questions
To start, connect both your Mobile Message and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Mobile Message triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Mobile Message 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 Mobile Message 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 Mobile Message 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 Mobile Message
Mobile Message is a comprehensive platform for managing and automating SMS communications, enabling businesses to effectively engage with their audience through personalized messaging solutions.
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.
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