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Compare Kafka Streams and Spark Structured Streaming for real-time processing

Spark/Big Datahard0.5 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Meesho
Key Concepts Tested
etlspark
Expert AnswerPremium
91 wordsInterview-ready
**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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