Learn about the fundamentals of Kafka, event streaming, and the surrounding ecosystem. Click on an element to find out more.
Create, import, share streams of events like payments, orders, and database changes in milliseconds, at scale. Store them as long as you need. Replay and reprocess historical data like a time machine.
Build lightweight, elastic applications and microservices that respond immediately to events and that scale during live operations. Process, join, and analyze streams and tables of data in real-time, 24x7.
Use one platform to set data in motion across your entire enterprise. Connect systems, data centers, and clouds—all with the same trusted technology. The largest production deployments handle trillions of events per day.
By kafka co-creator Jay Kreps, CEO of Confluent
Run pre-built ksqlDB recipes that tackle the highest impact use cases for stream processing
Write your first application using these full code examples in Java, Python, Go, .NET, Node.js, C/C++, REST, Spring Boot, and further languages and CLIs.
A rich catalog of design patterns to help you understand the interaction between the different parts of the Kafka ecosystem, so you can build better event streaming applications.
Explore the details of how Kafka works and how to monitor its performance.
Click on an element to learn more, or visit our Kafka Internals course.
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