**Why comparison matters**: Different operational models and best-fit use cases. **Kafka Streams**: Lightweight library; JVM; exactly-once; stateful; embeds in app. Good for microservices, low operational footprint. **Spark Structured Streaming**: Unified batch/stream API; rich ecosystem; larger footprint; micro-batch or continuous. Good for complex ETL, ML integration, team familiar with Spark. **Scalability trade-offs**: Kafka Streams = scale with app instances; Spark = scale with cluster....
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