Databricks
Amazon Personalize
Integrate your Databricks Data Warehouse with Amazon Personalize
Don't go through the pain of direct integration. RudderStack’s Reverse ETL connection makes it easy to send data from your Databricks Data Warehouse to Amazon Personalize and all of your other cloud tools.
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Easy Databricks to Amazon Personalize integration with RudderStackRudderStack’s open source Reverse ETL connection allows you to integrate RudderStack with your your Databricks Data Warehouse to track event data and automatically send it to Amazon Personalize. 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 Amazon Personalize and RudderStack
Enable real-time dataAutomatically send real-time data to marketing analytics, product analytics and business analytics tools.
Cross-platform trackingTrack the entire user journey across platforms without the technical headache.
Hot-swap analytics toolsSend existing data feeds to new analytics tools with a few clicks.
Frequently Asked Questions
With Rudderstack, integration between Databricks and Amazon Personalize is simple. Set up a Databricks source and start sending data.
Pricing Databricks and Amazon Personalize 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 Databricks and Amazon Personalize.
Use the Amazon Personalize integration with other popular sources
About Amazon Personalize

AWS Personalize is a machine learning service by Amazon Web Services. It enables you to create high-quality content recommendations, personalized product and marketing promotions, and much more. With AWS Personalize, you can boost your customer engagement and overall business revenue.

About Databricks

Storage layer that offers reliability and security on your data lake for streaming and batch operations