Connect Mobile Message and Google Cloud Bigtable 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 Google Cloud Bigtable
Enable Integrations or automations with these events of Mobile Message and Google Cloud Bigtable
Enable Integrations or automations with these events of Mobile Message and Google Cloud Bigtable
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 Google Cloud Bigtable accounts to viaSocket. Once connected, you can set up a workflow where an event in Mobile Message triggers actions in Google Cloud Bigtable (or vice versa).
Absolutely. You can customize how Mobile Message data is recorded in Google Cloud Bigtable. This includes choosing which data fields go into which fields of Google Cloud Bigtable, setting up custom formats, and filtering out unwanted information.
The data sync between Mobile Message and Google Cloud Bigtable 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 Google Cloud Bigtable. 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 Google Cloud Bigtable
Google Cloud Bigtable is a fully managed, scalable NoSQL database service designed for large analytical and operational workloads. It is ideal for applications that require high throughput and low latency, such as IoT, user analytics, and financial data analysis.
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