Data & AI

Micro-Batching vs Native Streaming

Data & AI Pipelines diagram · made in Skemio

Architecture comparison showing Kafka feeding into Spark micro-batch buffer and Flink continuous processing, writing to data sinks.
Architecture comparison showing Kafka feeding into Spark micro-batch buffer and Flink continuous processing, writing to data sinks.
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What it shows

  • Spark micro-batches buffer incoming records for 100ms-500ms intervals
  • Flink native streaming processes every event immediately as it arrives
  • Choose Flink for low-latency alerting; choose Spark for heavy aggregation

The takeaway

Don't pay the operational complexity of native streaming if 500ms batch windows solve your business problem.

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