S7E22 | Stream Processing Explained: Kafka Streams vs Spark vs Flink for Beginners

In this episode of PithorAcademy Presents: Deep Dive, we explore the world of stream processing and how popular frameworks like Kafka Streams, Apache Spark, and Apache Flink handle data. Understanding the differences between batch, near-real-time, and real-time systems helps developers pick the right tool for the job.

We cover:

• Kafka Streams vs Spark vs Flink – strengths and use cases

• Batch vs near-real-time vs real-time – processing models explained

• Kafka’s role in the stream processing ecosystem – where it fits and why it matters

By the end, you’ll understand the streaming landscape and how these tools compare when building real-time, data-driven applications.

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