Integrate your Databricks Data Warehouse with Madkudu
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 Madkudu and all of your other cloud tools.Easy Databricks to Madkudu 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 Madkudu. 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.Frequently Asked QuestionsAbout Databricks
Available via webhookSend event data to Madkudu by enabling webhooks in your RudderStack
dashboard, then using our Transformations feature to shape the payload
for the Madkudu API. Once enabled, RudderStack will forward events to
Madkudu (note, this requires leveraging cloud API endpoints for Madkudu
).
Popular ways to use Madkudu and RudderStackCreate leads automaticallyAutomatically create customer records in real time in Madkudu when someone signs up.
Trigger campaignsEnable your marketing team to trigger email, SMS, mobile, and personalization campaigns based on user actions.
Easily update user traitsProvide your marketing team with advanced segmentation capabilities by updating user traits in real time.
How do you integrate Databricks with Madkudu?
With Rudderstack, integration between Databricks and Madkudu is simple. Set up a Databricks source and start sending data.
Is it expensive to integrate Databricks with Madkudu?
Pricing Databricks and Madkudu 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 Madkudu?
Timing can vary based on your tech stack and the complexity of your data needs for Databricks and Madkudu.
About Madkudu
Madkudu is a predictive lead scoring solution that helps B2B market leaders to accelerate growth using their customer data. It applies machine learning algorithms to customer data to score leads based on past activity or attributes.
Storage layer that offers reliability and security on your data lake for streaming and batch operations
