Chapter Four
Encoding and Evolution
Applications change, and data formats need to evolve with them. How do we maintain compatibility as systems evolve? This chapter explores encoding formats and dataflow patterns that enable change without breaking.
Data Encoding Formats
JSON
JavaScript Object Notation - human-readable, widely supported
XML
Extensible Markup Language - strict, verbose, with validation
Protocol Buffers
Binary format from Google - compact, fast, with schemas
Avro
Binary format from Hadoop - schema embedded with data
Thrift
Cross-language RPC framework from Facebook
Modes of Dataflow
Database to Database
Replication, ETL, change data capture
Through Services
REST, RPC, GraphQL APIs
Message Passing
Kafka, RabbitMQ, event-driven
Compatibility Checklist
When evolving your data formats, consider these compatibility requirements:
Encoding Format
Dataflow Protocol
Part I Complete!
You've covered the foundations of data systems: reliability, scalability, maintainability, data models, storage engines, and encoding evolution. Ready to explore distributed systems?