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Apache Kafka and Apache Flink are increasingly being used together to build innovative real-time stream processing applications. This blog post explores the benefits of combining both open-source frameworks, shows unique differentiators of Flink versus Kafka, and discusses when to use a Kafka-native streaming engine like Kafka Streams instead of Flink. Stream processing is a paradigm that continuously correlates events of one or more data sources, and is processed in motion, in contrast to traditional processing at rest with a database and request-response API.
