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

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PithorAcademy Presents: Deep Dive

PithorAcademy

266 episodes

40 minutes ago

Welcome to Deep Dive, presented by PithorAcademy. Our mission is to simplify the latest technologies—why they were created, the problems they solve, and how they work—so you're always interview-ready and ahead in your tech journey. Whether you're a Java enthusiast, a cloud-native developer, or scaling microservices, gain real insights from those shaping the tech world. Join us as we unpack topics like Java development, cloud architecture, DevOps, system design, API strategy, career growth, and the ever-evolving tech landscape. Hosted by the PithorAcademy team.

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

PithorAcademy Presents: Deep Dive

6 minutes 35 seconds

2 weeks ago

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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