Spark Streaming vs Flink

Concepts: paMicroBatchVsTrue

What They Want to Hear 'Spark Structured Streaming is micro-batch: it collects events for a trigger interval (e.g., 10 seconds), processes them as a batch, then starts the next interval. Flink processes each event as it arrives with continuous operator pipelines. The practical differences: Spark has a 100ms latency floor and simpler state management. Flink has sub-10ms latency, more powerful windowing (session windows, event-time processing), and built-in savepoints for state migration. I choose Spark when the team already runs Spark for batch and latency requirements are relaxed. I choose Flink when latency is critical or the streaming logic requires complex stateful processing.' This is the answer that shows you can make a technology choice with concrete tradeoff reasoning.