Kafka for Developers - Data Contracts Using Schema Registry - Data Evolution and Schema Evolution

The lecture covers the data life cycle and schema evolution, emphasizing the importance of adapting to changing business requirements. It explains how schemas evolve with data changes and the role of Schema Registry in managing these changes. Various compatibility types are discussed, including backward, forward, and full transitive, highlighting their impact on producers and consumers. The lecture aims to provide practical knowledge on applying these compatibility types to ensure seamless schema evolution without affecting applications.

What are the different compatibility types supported in Schema Registry?

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How does backward compatibility differ from forward compatibility?

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What is the ultimate goal when evolving the schema according to the lecture?

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