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  1. Stackups
  2. Application & Data
  3. Frameworks
  4. Serialization Frameworks
  5. Apache Thrift vs Protobuf

Apache Thrift vs Protobuf

OverviewComparisonAlternatives

Overview

Apache Thrift
Apache Thrift
Stacks193
Followers245
Votes0
GitHub Stars10.8K
Forks4.1K
Protobuf
Protobuf
Stacks3.8K
Followers393
Votes0
GitHub Stars69.5K
Forks15.9K

Apache Thrift vs Protobuf: What are the differences?

Introduction

Apache Thrift and Protobuf are two popular serialization frameworks that provide language and platform-independent communication between applications. While both frameworks serve a similar purpose, there are key differences that set them apart.

  1. Language Support: Apache Thrift supports more programming languages compared to Protobuf. Thrift provides support for languages such as C++, Java, Python, and Ruby, while Protobuf supports languages like C++, Java, Python, and Go. This broader language support can be advantageous in projects where multiple languages are involved.

  2. Data Encoding: Thrift uses a binary encoding format by default, whereas Protobuf supports both binary and text encoding. Binary encoding is more compact and efficient, resulting in smaller message sizes and faster transmission. On the other hand, text encoding provides better human-readability and is easier for debugging purposes.

  3. IDL Syntax: The syntax used to define interfaces and structures in Thrift and Protobuf differs. Thrift uses an IDL (Interface Definition Language) similar to C or C++, with a focus on protocol versioning. Protobuf utilizes a simpler and more concise syntax based on the Protocol Buffers language.

  4. Extensibility and Compatibility: Protobuf provides better extensibility and backward compatibility compared to Thrift. Protobuf messages can be extended by adding new fields, while Thrift requires modifying the entire schema. This flexibility in Protobuf allows for easier evolution of data structures without breaking existing code.

  5. Code Generation: Thrift generates code specific to different programming languages, including client and server stubs, serialization/deserialization code, and more, while Protobuf generates data access classes specific to the target language. This difference in code generation can impact the development workflow and integration with existing codebases.

  6. Ecosystem and Community: Both Thrift and Protobuf have active communities and are widely used in industry, but Thrift has a larger ecosystem with additional tools and libraries available. This broader ecosystem can provide better support and resources for developers working with Thrift.

In summary, the key differences between Apache Thrift and Protobuf include language support, data encoding options, IDL syntax, extensibility and compatibility, code generation approach, and ecosystem/community size. These factors can influence the choice of serialization framework based on specific project requirements and development considerations.

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Detailed Comparison

Apache Thrift
Apache Thrift
Protobuf
Protobuf

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.

Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.

Statistics
GitHub Stars
10.8K
GitHub Stars
69.5K
GitHub Forks
4.1K
GitHub Forks
15.9K
Stacks
193
Stacks
3.8K
Followers
245
Followers
393
Votes
0
Votes
0

What are some alternatives to Apache Thrift, Protobuf?

MessagePack

MessagePack

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.

Avro

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.

Serde

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

Sonic

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

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