Why Kafka Handles Millions of Writes per Second: I/O Secrets Revealed

This article explains how Kafka achieves ultra‑high throughput by using sequential disk writes, memory‑mapped files, zero‑copy sendfile reads, and batch compression, while also describing its data retention policies and the trade‑offs of synchronous versus asynchronous producer modes.

Batch CompressionHigh ThroughputMemory Mapped Files

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Why Kafka Handles Millions of Writes per Second: I/O Secrets Revealed

Big Data Technology Architecture

May 23, 2019 · Big Data

Kafka Performance Design: Sequential I/O, Page Cache, Zero‑Copy, and Partition Segmentation

The article explains how Kafka achieves high throughput and low latency by leveraging sequential disk I/O, operating‑system page cache, zero‑copy transmission, and a partition‑segment storage model, all of which are key design choices for big‑data messaging systems.

big-datapage cachesequential-io

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Kafka Performance Design: Sequential I/O, Page Cache, Zero‑Copy, and Partition Segmentation