Schema Evolution: Backward and Forward Compatibility
Evolve data schemas safely: add optional fields, deprecate old ones, and maintain backward and forward compatibility in JSON, Avro, and Protobuf.
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Tags: data, schema, compatibility
Schema Evolution Guide: Backward and Forward Compatibility in Data Formats Schemas change. New fields get added, old ones get removed, types get widened, column names get fixed. The problem isn't the change — it's what happens to existing data producers and consumers when the change lands. This guide explains backward and forward compatibility, why they matter, and how Avro, Protobuf, and JSON Schema each handle schema evolution. It also covers the practical strategies that keep pipelines running through changes. --- The Compatibility Problem Imagine a Kafka topic where producers write order events and ten downstream consumers read them. The order schema adds a new field: . What happens? New producer, old consumer: The consumer reads messages with a field it doesn't know about. Does it…
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