S7E14 | Apache Kafka Data Lifecycle: Retention Policies & Log Compaction Explained

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PithorAcademy Presents: Deep Dive

PithorAcademy

266 episodes

10 hours 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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S7E14 | Apache Kafka Data Lifecycle: Retention Policies & Log Compaction Explained

PithorAcademy Presents: Deep Dive

5 minutes 49 seconds

4 weeks ago

S7E14 | Apache Kafka Data Lifecycle: Retention Policies & Log Compaction Explained

In this episode of PithorAcademy Presents: Deep Dive, we explore Kafka’s Data Lifecycle, focusing on how retention and log compaction manage stored events in Apache Kafka. Kafka isn’t just a queue—it’s also a distributed log, and understanding how data is kept or removed is key to building reliable systems.

We cover:

Retention Policies – controlling how long Kafka stores data
Log Compaction – retaining the latest state of each key
Kafka as a Queue vs a Log – why lifecycle management matters

By the end, you’ll understand how Kafka balances storage efficiency, reliability, and stateful processing—making it powerful for streaming platforms like Uber, Netflix, and LinkedIn.

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