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
How can you count the number of events in a Kafka topic based on some criteria?
How can you dynamically route records to different Kafka topics, like a "topic exchange"?
How do you get started in building your first Kafka Streams application?
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.
Design patterns help you plan, implement, and communicate about software architectures. The main groups of patterns for event streaming are shown in this diagram, including compositional patterns that apply across several areas.
Click on each group to find out more.
Explore the details of how Kafka works and how to monitor its performance. Click on an element to learn more.
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