Serialization trade-offs in distributed systems: A comparative analysis of JSON, Protocol Buffers, and FlatBuffers under varying width and nesting depth

This discussion paper compares three common serialization paradigms - JSON, Protocol Buffers, and FlatBuffers - with respect to latency and space efficiency. Although serialization is central to modern distributed systems, controlled, paradigm-level comparisons remain limited. To address this, the study benchmarks all three formats in Rust while systematically varying record width and nesting depth. Quantitative measurements are complemented by CPU profiling to identify dominant cost drivers. Results show clear patterns: Protocol Buffers achieves the lowest serialization latency and smallest message sizes, FlatBuffers offers the fastest data access due to its zero-copy design, and JSON incurs the highest access costs and largest payloads. Each format therefore excels under different conditions: Protobuf in write-and bandwidth-sensitive scenarios, FlatBuffers in read-dominated contexts, and JSON where readability and flexibility matter.