My book, Designing Data-Intensive Applications, was published by O’Reilly in March 2017.
Martin Kleppmann and Jay Kreps
IEEE Data Engineering Bulletin 38(4):4–14, December 2015.
Apache Kafka is a scalable message broker, and Apache Samza is a stream processing framework built upon Kafka. They are widely used as infrastructure for implementing personalized online services and real-time predictive analytics. Besides providing high throughput and low latency, Kafka and Samza are designed with operational robustness and long-term maintenance of applications in mind. In this paper we explain the reasoning behind the design of Kafka and Samza, which allow complex applications to be built by composing a small number of simple primitives – replicated logs and stream operators. We draw parallels between the design of Kafka and Samza, batch processing pipelines, database architecture, and the design philosophy of Unix.