Streaming Frameworks Explained
Kafka serves as a standalone streaming framework, while Spark traditionally uses micro-batching for stream processing. Yi highlights the differences between Spark's micro-batch approach and Samza's pure event-by-event streaming, emphasizing the operational challenges of synchronizing batch boundaries. The discussion also touches on the origins of Kafka Streams, which emerged from the need for simpler stream processing solutions in smaller use cases.In this clip
From this podcast
Software Engineering Radio - the podcast for professional software developers
Episode 436: Apache Samza with Yi Pan
Related Questions