Kafka Streams API vs Spark Streaming
An example of an AI chatbot conversation about comparing Kafka Streams API and Spark Streaming.
What are the main differences between Kafka Streams API and Spark Streaming?
Kafka Streams API is designed for real-time processing of data streams directly from Kafka, while Spark Streaming is a micro-batch processing framework that can handle data from various sources.
Which one is better for low-latency processing?
Kafka Streams API generally offers lower latency since it processes data in real-time, whereas Spark Streaming introduces some latency due to its micro-batch processing.
Can you explain the scalability of both frameworks?
Both frameworks are scalable, but Kafka Streams scales horizontally with Kafka brokers, while Spark Streaming requires a Spark cluster, which can add complexity.
What are some use cases for each?
Kafka Streams is great for real-time analytics and event-driven applications, while Spark Streaming is suitable for batch processing and complex event processing.
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