Insights into Protocol Buffers (Protobuf)

I had the opportunity to work with Protocol Buffers (Protobuf) recently, and I wanted to share some insights and a quick guide for those who might be new to it.

Protocol Buffers: Quick Guide

Protobuf is a compact and strongly typed way to serialize structured data. It’s widely used with gRPC and backend services where performance and schema stability matter more than human readability. Pioneered by Google.

Why Protobuf?

• Smaller and faster than JSON or XML
• Strongly typed schemas
• Built-in backward and forward compatibility
• Language- and platform-neutral

Minimal Example

message User {
  int32 id = 1;
  string firstname = 2;
  string lastname = 3;
  bool is_active = 4;
}

A .proto file defines your data structure. Field numbers are required, must be unique, and should never change once published.

Binary Format Layer

With Protobuf, you define your data structure in a .proto file. You then use the Protobuf compiler (protoc) to generate code in your target programming language (e.g., Python, Java, Go, C++, etc.). This generated code includes classes for your messages and methods to serialize and deserialize them.

Due to its binary format, Protobuf is much more compact than text-based formats like JSON or XML, making it ideal for high-performance applications, although it sacrifices human readability.

Language-Neutral, but still Opinionated

Each field has a type (int32, string, bool, etc.) and a unique number. Protobuf supports nested messages, enums, repeated fields (arrays), and maps (dictionaries). There’s a few quirks to be aware of:

• field names are cosmetic only; serialization relies on field numbers
• field numbers 19000-19999 are reserved for internal use
• default values are used when fields are missing (e.g., 0 for numbers, empty string for strings, false for booleans)
• binary format is not human-readable
• hard limits and sizes
• focus on compatibility; fields never get removed or re-used, only deprecated