Schema Evolution Guide: Backward and Forward Compatibility in Data Formats
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. Backward Compatibility A schema change is backward compatible if consumers using the new schema can still read records written with the old schema. Changes That Are Backward Compatible Adding a new optional field with a default value Making a required field optional Widening a…
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