serialization

JSON offers human-readable text format ideal for APIs and web services, Protocol Buffers provide compact binary serialization with strong schema support, and MessagePack delivers efficient binary compression for high-throughput systems. Choose JSON for simplicity and debuggability, Protocol Buffers for strict versioning and cross-language compatibility, and MessagePack for bandwidth-constrained environments.

Schema evolution strategies maintain backward and forward compatibility by allowing optional fields, versioning mechanisms, and graceful field handling. Protocol Buffers enforce this natively through field numbering and optional semantics. Plan field additions carefully, avoid removing fields, and use versioning schemes to support multiple data formats simultaneously across service boundaries.

Serialize dates consistently using ISO8601 standard format, which works across JSON, Protocol Buffers, and MessagePack. Store timezone information explicitly and standardize on UTC internally to avoid ambiguity. This ensures reliable interchange between systems and languages without platform-specific datetime parsing issues.

Yes, custom serializers extend built-in format capabilities for domain-specific types. Implement serialization logic that converts complex objects to supported primitives, handles edge cases, and maintains compatibility with schema evolution rules. Document custom serializer behavior to ensure consistency across teams and services.

Enforce consistent naming conventions—snake_case for JSON APIs, camelCase for JavaScript, or language-native styles with explicit mapping rules. Define these conventions upfront and enforce them through schema definitions and serialization frameworks to prevent field-name mismatches during cross-language data exchange.

Null semantics differ across formats: JSON explicitly supports null, Protocol Buffers use optional fields and presence tracking, and MessagePack treats null as a distinct type. Define explicit null-handling policies—distinguish between missing fields and intentional nulls—and document assumptions to avoid silent data loss during deserialization.