Schema Evolution
Schema evolution is the practice of managing changes to data structures (schemas) over time in systems like databases, data lakes, or message queues, while maintaining backward and forward compatibility. It involves techniques to modify schemas—such as adding, removing, or altering fields—without breaking existing applications or data pipelines. This is crucial in distributed systems and data-intensive environments where data formats evolve as business requirements change.
Developers should learn schema evolution to handle data changes safely in production systems, especially in microservices, data warehouses, or event-driven architectures. It's essential when using technologies like Apache Avro, Protobuf, or JSON Schema, where schema updates must not disrupt consumers or producers, ensuring data integrity and minimizing downtime during deployments.