PipeDream
Apache Kafka
Integrate PipeDream with Apache Kafka
Don't go through the pain of direct integration. RudderStack’s PipeDream integration makes it easy to send data from PipeDream to Apache Kafka and all of your other cloud tools.
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Easy PipeDream to Apache Kafka integration with RudderStackRudderStack’s open source PipeDream integration allows you to integrate RudderStack with your PipeDream to track event data and automatically send it to Apache Kafka . With the RudderStack PipeDream integration, 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 Apache Kafka and RudderStack
Easily trigger automationsAutomatically trigger automations in Apache Kafka with data from RudderStack.
Send rich metadataUse existing data as part of Apache Kafka automations.
Enable custom logicUse existing data to drive custom logic in Apache Kafka .
Frequently Asked Questions
With Rudderstack, integration between PipeDream and Apache Kafka is simple. Set up a PipeDream source and start sending data.
Pricing PipeDream and Apache Kafka 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 PipeDream and Apache Kafka .
Use the Apache Kafka integration with other popular sources
About Apache Kafka

Apache Kafka is a popular distributed streaming platform. It allows you to handle large-scale workloads with high throughput and low latency. Apache Kafka is highly available and is used across the world for building real-time data pipelines and streaming applications.

About PipeDream

Pipedream lets you automate pre-built actions that connect APIs. If a pre-built source is not available for your use case, you can build your own. PipeDream supports open source triggers and actions for hundreds of integrations. It allows you to connect applications, APIs, and event sources in order to run workflows.