There are just too many messaging format that we can choose from when building a project. The table below summarize a quick cheat sheet on which messaging format to choose for different use cases.
| Format | BSON | MessagePack | Apache Avro | Protocol Buffers (protobuf) | JSON |
|---|
| Features | - Binary format with rich data types | - Compact, lightweight binary format | - Binary serialization format with schema | - Strongly typed, schema-driven format | - Human-readable text format |
| - Supports complex data structures | - Supports common data types | - Self-describing format with schema | - Code generation based on schema | - Simplicity and ease of debugging |
| - Supports specific MongoDB types | - Schemaless (no predefined schema) | - Support for evolution of data schema | - Type safety and structured data | - Requires minimal encoding/decoding overhead |
| - Field names included, leading to larger data size | - Language-agnostic with wide language support | - Language support in multiple programming languages | | - Widespread language support |
| Common Use Cases | - MongoDB data storage and exchange | - Cross-platform data interchange | - Data storage and exchange (Hadoop, Kafka, etc.) | - High-performance data serialization (e.g., gRPC) | - Web APIs and data interchange |
| - Specifically suited for MongoDB ecosystem | - Microservices communication | - Big data processing and analytics (Apache ecosystem) | - Language-agnostic communication in large-scale systems | - Configuration files and settings |
| | - IoT and embedded systems | - When schema evolution and versioning are important | - Google ecosystem and related projects (e.g., gRPC) | - When human readability is important |
