Flink vs Kafka Streams: A Complete Comparison

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This post provides a detailed comparison between Apache Flink and Kafka Streams, focusing on their architectural differences and ideal use cases. It elaborates on Flink's cluster-based deployment, job lifecycle management, and its capabilities for high throughput, low latency, and exactly-once semantics. It contrasts this with Kafka Streams, which is presented as an embeddable library that leverages Kafka for coordination, load balancing, and fault tolerance, simplifying stream processing for application developers. Key differences in deployment, lifecycle, coordination, data sources/sinks, and semantic guarantees are outlined.