The Evolution of Stream Processing Systems

This chapter explores the evolution and current challenges of stream processing systems, focusing on technologies like Kafka and Flink. It emphasizes the importance of developer productivity in real-time data environments and critiques the limitations of SQL as a framework for stream processing. The discussion highlights the need for better-designed APIs and the ongoing transition in analytics roles, particularly towards analytics engineers, in response to the complexities of modern data engineering.

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