Connect Sympla and Google Cloud Bigtable to Build Intelligent Automations
Choose a Trigger
When this happens...
New Event
New Orders
Choose an Action
Automatically do this!
- Request a new Action for Google Cloud Bigtable
Enable Integrations or automations with these events of Sympla and Google Cloud Bigtable
Enable Integrations or automations with these events of Sympla and Google Cloud Bigtable
Triggers
New Event
Fetch events that were created or updated since the last check.
New Orders
Fetch ticket orders for the selected Sympla event that were created since the last check.
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Frequently Asked Questions
To start, connect both your Sympla and Google Cloud Bigtable accounts to viaSocket. Once connected, you can set up a workflow where an event in Sympla triggers actions in Google Cloud Bigtable (or vice versa).
Absolutely. You can customize how Sympla 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 Sympla 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 Sympla 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 Sympla
Sympla is a comprehensive platform for event management and ticketing, offering tools to organize, promote, and manage events of all sizes. It provides features for ticket sales, attendee management, and event promotion, making it ideal for event organizers and marketers.
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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