Spark Versus Flink

Sibanjan Das compares Apache Flink to Apache Spark:

The primitive concept of Apache Flink is the high-throughput and low-latency stream processing framework which also supports batch processing. The architecture is a flip of the other Big Data processing architectures where the primary notion was the batch processing framework. This is something that organizations have been looking for over the last decade. There is a need for platforms supporting low latency data movement for applications where even a millisecond delay can lead to severe consequences. The prospect of Apache Flink seems to be significant and looks like the goal for stream processing.

While comparing these two, don’t forget about Kafka Streams.  We’ve entered the streaming era for Hadoop & friends, and it’s an exciting time.

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