Why Is Kafka So Fast?
Last updated: January 25, 2026 Read in fullscreen view
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While Java itself is often criticized for being slow due to garbage collection (GC) and JVM overhead, it was still chosen to build Kafka - a distributed real-time streaming platform with extremely high performance.
Kafka achieves high performance in Java not by fighting Java’s limitations, but by designing around them and fully leveraging the power of the operating system.
The core idea is to minimize the amount of data that enters the Java application heap.
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Zero-copy: Kafka uses the
sendfilesystem call via Java’sFileChannel, allowing data to flow directly from the OS page cache to the network card without passing through the JVM heap. This reduces data copying, lowers GC pressure, and minimizes context switches between user space and kernel space. Java mainly acts as a coordinator. -
Sequential reads and writes: Kafka stores data as a sequential log and only appends to the end of files, avoiding unnecessary random I/O.
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Leveraging the OS page cache: Kafka does not cache data in the Java process itself. Instead, it relies on the OS page cache. When Kafka writes data, it writes to the page cache; when it reads data, it reads from the page cache. This completely avoids forcing the Java GC to scan through gigabytes of cached data.
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Batching and non-blocking I/O: Kafka batches data before sending it over the network instead of sending messages one by one, reducing unnecessary I/O. In addition, Java NIO allows a single thread to manage thousands of connections using non-blocking I/O. This is why Kafka can handle tens of thousands of concurrent connections without crashing the JVM.
Kafka is fast not because Java is fast, but because Kafka uses Java as a control and orchestration tool rather than a data-moving engine.
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