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What problem does schema evolution solve in Kafka data streams?

easy🧠 Conceptual Q2 of Q15
Kafka - Schema Registry
What problem does schema evolution solve in Kafka data streams?
AIt compresses data to reduce storage costs.
BIt automatically retries failed messages.
CIt allows changes in data structure without breaking existing consumers.
DIt encrypts data for security.
Step-by-Step Solution
Solution:

  1. Step 1: Define schema evolution

    Schema evolution means updating data format while keeping compatibility.

  2. Step 2: Understand its role in Kafka

    It prevents breaking consumers when producers change data structure.

  3. Final Answer:

    It allows changes in data structure without breaking existing consumers. -> Option C

  4. Quick Check:

    Schema evolution = Safe data structure changes [OK]
Quick Trick: Schema evolution avoids breaking consumers [OK]
Common Mistakes:
MISTAKES
  • Confusing schema evolution with data compression
  • Thinking it retries messages automatically
  • Assuming it encrypts data

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