Integrate your Databricks Data Warehouse with Gladly
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 Gladly and all of your other cloud tools.Easily integrate Databricks with Gladly using 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 Gladly. 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 Gladly and RudderStackFrequently Asked QuestionsAbout Databricks
Create and update customersCreate and update customers in Gladly in real time.
Track customer behaviorSend key user actions to Gladly to give the customer success team context for support tickets.
Assign users to groupsAutomatically assign new users to existing groups, companies or accounts in Gladly.
How do you integrate Databricks with Gladly?
With Rudderstack, integration between Databricks and Gladly is simple. Set up a Databricks source and start sending data.
Is it expensive to integrate Databricks with Gladly?
Pricing Databricks and Gladly can vary based on the way they charge. Check out our pricing page for more info. Or give us a try for FREE.
How long does it take to integrate Databricks with Gladly?
Timing can vary based on your tech stack and the complexity of your data needs for Databricks and Gladly.
About Gladly
Gladly is a customer service platform that leverages AI to deliver personalized agent-assisted customer service and enhance customer relationships. Gladly incorporates the strengths of AI without losing the human interaction to deliver quality customer service. RudderStack supports Gladly as a destination to which you can seamlessly send your customer data.
Storage layer that offers reliability and security on your data lake for streaming and batch operations