Integrate your Google BigQuery Data Warehouse with Tray.io
Don't go through the pain of direct integration. RudderStack’s Reverse ETL connection makes it easy to send data from your Google BigQuery Data Warehouse to Tray.io and all of your other cloud tools.
Easy Google BigQuery to Tray.io integration with RudderStack
RudderStack’s open source Reverse ETL connection allows you to integrate RudderStack with your Google BigQuery Data Warehouse to track event data and automatically send it to Tray.io. With the RudderStack Reverse ETL connection, you do not have to worry about having to learn, test, implement or deal with changes in a new API and multiple endpoints every time someone asks for a new integration.
Popular ways to use Tray.io
Automatically trigger automations in Tray.io with data from RudderStack.
Use existing data as part of Tray.io automations.
Use existing data to drive custom logic in Tray.io.
Frequently Asked Questions
With Rudderstack, integration between Google BigQuery source and Tray.io is simple. Set up a Google BigQuery source source and start sending data.
Pricing Google BigQuery source and Tray.io can vary based on the way they charge. Check out our pricing page for more info. Or give us a try for FREE.
Timing can vary based on your tech stack and the complexity of your data needs for Google BigQuery source and Tray.io.
Tray.io is a leading automation and API integration platform for modern enterprises. It allows you to integrate and bring together your tech stack and automate workflows and processes with its visual editor. From setting up simple point-to-point integrations to building complex workflows using a predetermined conditional logic, Tray.io allows you to design a robust data flow across different teams for all your use cases. With Tray.io, you can essentially automate your entire organization without having to strain your development resources.
About Google BigQuery
Google BigQuery is a fully-managed cloud data warehouse that allows you to store and analyze petabytes of data in no time. It is serverless, highly scalable, and cost-effective and is designed for businesses to analyze massive datasets and make informed business decisions. Google BigQuery also allows running complex analytical SQL-based queries using built-in machine learning capabilities.