Flink is similar to Spark Streaming and is an event-driven real-time streaming system.

Question

Options

• ATrue
• BFalse

• A
  28% (8)
• B
  72% (21)

Explanation

B is correct because the statement conflates two architecturally different systems. Flink and Spark Streaming are not similar in a meaningful way: Spark Streaming uses micro-batching - it slices the incoming stream into small time-window batches and processes them like mini batch jobs - whereas Flink is a true stream processing engine that processes each event individually as it arrives, with no batching layer underneath.

Why A is wrong: Calling them "similar" obscures the critical architectural difference. Spark Streaming's micro-batch model introduces latency and behaves more like repeated batch processing, while Flink's native streaming model achieves lower, more consistent latency with exactly-once semantics at the event level.

Memory tip: Think "Flink = Flow, Spark Streaming = Spurts." Flink processes data as a continuous flow of individual events; Spark Streaming processes data in periodic spurts (micro-batches). If an exam question tries to group them together as equivalent streaming solutions, flag it as false.

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