Overview

MessagePack

Stacks24

Followers79

Votes1

GitHub Stars7.3K

Forks521

Protobuf

Stacks2.7K

Followers393

Votes0

GitHub Stars69.5K

Forks15.9K

MessagePack vs Protobuf: What are the differences?

Both MessagePack and Protobuf are popular data interchange formats that offer compact and efficient serialization and deserialization of structured data. Let's explore the key differences between MessagePack and Protobuf.

Data Representation: MessagePack uses a binary format for data representation, whereas Protobuf uses a combination of binary and textual formats.
Schema Definition: MessagePack does not require a schema definition for serialization and deserialization, making it more flexible for loosely structured data. On the other hand, Protobuf requires a strict schema definition using a .proto file, enforcing a structured and strongly typed data model.
Compatibility: MessagePack supports backward and forward compatibility out of the box, allowing for seamless communication between different versions or implementations of the data format. In contrast, Protobuf requires careful management of schema evolution and versioning to ensure compatibility.
Language Support: MessagePack has extensive language support, with libraries available for many programming languages. Protobuf also has broad language support, but it is primarily focused on the languages supported by Google, such as Java, C++, and Python.
Serialization Efficiency: MessagePack provides a highly efficient binary serialization format, resulting in smaller message sizes. Protobuf also offers efficient serialization but may have slightly larger message sizes due to the inclusion of field tags and length prefixes.
Rich Feature Set: Protobuf offers a richer feature set compared to MessagePack, with support for features like default values, nested messages, and enums. MessagePack, on the other hand, provides a more minimalistic approach, focusing on simplicity and performance.

In summary, MessagePack and Protobuf differ significantly in data representation, schema definition requirements, compatibility, language support, serialization efficiency, and feature sets. Understanding these differences can help you make an informed decision on which data format to choose for your specific application needs.

Detailed Comparison

MessagePack	Protobuf
It is an efficient binary serialization format. It lets you exchange data among multiple languages like JSON. But it's faster and smaller. Small integers are encoded into a single byte, and typical short strings require only one extra byte in addition to the strings themselves.	Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.
Binary serialization format; Exchange data among multiple languages ; Faster and smaller	-
Statistics
GitHub Stars 7.3K	GitHub Stars 69.5K
GitHub Forks 521	GitHub Forks 15.9K
Stacks 24	Stacks 2.7K
Followers 79	Followers 393
Votes 1	Votes 0
Pros & Cons
Pros 1 Lightweight	No community feedback yet
Integrations
Redis Ruby Fluentd Haskell	No integrations available

What are some alternatives to MessagePack, Protobuf?

Avro

It is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format.

Apache Thrift

The Apache Thrift software framework, for scalable cross-language services development, combines a software stack with a code generation engine to build services that work efficiently and seamlessly between C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml and Delphi and other languages.

Serde

It is a framework for serializing and deserializing Rust data structures efficiently and generically. The ecosystem consists of data structures that know how to serialize and deserialize themselves along with data formats that know how to serialize and deserialize other things. It provides the layer by which these two groups interact with each other, allowing any supported data structure to be serialized and deserialized using any supported data format.

Sonic

It is a blazingly fast JSON serializing & deserializing library, accelerated by JIT (just-in-time compiling) and SIMD (single-instruction-multiple-data).