Software Alternatives, Accelerators & Startups

Apache Thrift VS Protobuf

Compare Apache Thrift VS Protobuf and see what are their differences

Apache Thrift logo Apache Thrift

An interface definition language and communication protocol for creating cross-language services.

Protobuf logo Protobuf

Protocol buffers are a language-neutral, platform-neutral extensible mechanism for serializing structured data.
  • Apache Thrift Landing page
    Landing page //
    2019-07-12
  • Protobuf Landing page
    Landing page //
    2023-08-29

Apache Thrift features and specs

  • Cross-Language Support
    Apache Thrift supports numerous programming languages including Java, Python, C++, Ruby, and more, enabling seamless communication between services written in different languages.
  • Efficient Serialization
    Thrift offers efficient binary serialization which helps in reducing the payload size and improves the communication speed between services.
  • Service Definition Flexibility
    Thrift provides a robust interface definition language (IDL) for defining and generating code for services with strict type checking, fostering strong contract interfaces.
  • Scalability
    Due to its lightweight and efficient serialization mechanisms, Apache Thrift can handle a large number of simultaneous client connections, making it suitable for scalable distributed systems.
  • Versioning Support
    Thrift supports service versioning which helps in evolving APIs without disrupting existing services or clients.

Possible disadvantages of Apache Thrift

  • Steep Learning Curve
    For new users, especially those not familiar with RPC frameworks, learning and understanding Thrift’s IDL and operations can be complex and time-consuming.
  • Documentation and Community Support
    Compared to some alternative technologies, Apache Thrift's documentation and community support can be less robust, which might pose challenges in troubleshooting or seeking guidance.
  • Lack of Advanced Features
    Thrift does not support some advanced features like streaming or multiplexing out of the box, which could limit its use in complex systems requiring these functionalities.
  • Infrastructure Overhead
    Integrating Thrift into an existing system might introduce infrastructure overhead both in initial setup and ongoing maintenance, especially when dealing with multiple languages.
  • Protocol Limitations
    While Thrift is highly efficient, its protocol limitations might require additional workarounds for certain data structures or transport mechanisms, complicating development.

Protobuf features and specs

  • Efficient Serialization
    Protobuf is known for its high efficiency in serializing structured data. It is faster and produces smaller size messages compared to JSON or XML, making it ideal for bandwidth-limited and resource-constrained environments.
  • Language Support
    Protobuf supports multiple programming languages including Java, C++, Python, Ruby, and Go. This makes it versatile and useful in heterogeneous environments.
  • Versioning Support
    It natively supports schema evolution without breaking existing implementations. Fields can be added or removed over time, ensuring backward and forward compatibility.
  • Type Safety
    Being a strongly typed data format, Protobuf ensures that data is correctly typed across different systems, preventing serialization and deserialization errors common with loosely typed formats.

Possible disadvantages of Protobuf

  • Learning Curve
    Protobuf requires learning and understanding its schema definitions and compiler usage, which might be a challenge for new developers.
  • Lack of Human Readability
    Serialized Protobuf data is in a binary format, making it less readable and debuggable compared to JSON or XML without specialized tools.
  • Limited Built-in Support for Complex Data Types
    By default, Protobuf does not provide comprehensive support for handling complex data types like maps or unions compared to some other data serialization formats, requiring workarounds.
  • Tooling Requirement
    Using Protobuf necessitates a compilation step where `.proto` files are converted into code, requiring additional tooling and build system integration.

Apache Thrift videos

Apache Thrift

Protobuf videos

StreamBerry, part 2 : introduction to Google ProtoBuf

Category Popularity

0-100% (relative to Apache Thrift and Protobuf)
Web Servers
66 66%
34% 34
Configuration Management
0 0%
100% 100
Web And Application Servers
Mobile Apps
0 0%
100% 100

User comments

Share your experience with using Apache Thrift and Protobuf. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Protobuf should be more popular than Apache Thrift. It has been mentiond 83 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Thrift mentions (13)

  • Show HN: TypeSchema – A JSON specification to describe data models
    I once read a paper about Apache/Meta Thrift [1,2]. It allows you to define data types/interfaces in a definition file and generate code for many programming languages. It was specifically designed for RPCs and microservices. [1]: https://thrift.apache.org/. - Source: Hacker News / 6 months ago
  • Delving Deeper: Enriching Microservices with Golang with CloudWeGo
    While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future. - Source: dev.to / about 1 year ago
  • Reddit System Design/Architecture
    Services in general communicate via Thrift (and in some cases HTTP). Source: about 2 years ago
  • Universal type language!
    Protocol Buffers is the most popular one, but there are many others such as Apache Thrift and my own Typical. Source: about 2 years ago
  • You worked on it? Why is it slow then?
    RPC is not strictly OO, but you can think of RPC calls like method calls. In general it will reflect your interface design and doesn't have to be top-down, although a good project usually will look that way. A good contrast to REST where you use POST/PUT/GET/DELETE pattern on resources where as a procedure call could be a lot more flexible and potentially lighter weight. Think of it like defining methods in code... Source: over 2 years ago
View more

Protobuf mentions (83)

  • JSON vs Protocol Buffers vs FlatBuffers: A Deep Dive
    Protocol Buffers, developed by Google, is a compact and efficient binary serialization format designed for high-performance data exchange. - Source: dev.to / about 2 months ago
  • Developing games on and for Mac and Linux
    Protocol Buffers: https://developers.google.com/protocol-buffers. - Source: dev.to / about 2 years ago
  • Adding Codable conformance to Union with Metaprogramming
    ProtocolBuffers’ OneOf message addresses the case of having a message with many fields where at most one field will be set at the same time. - Source: dev.to / over 2 years ago
  • Logcat is awful. What would you improve?
    That's definitely the bigger thing. I think something like Protocol Buffers (Protobuf) is what you're looking for there. Output the data and consume it by something that can handle the analysis. Source: over 2 years ago
  • Bitcoin is the "narrow waist" of internet-based value
    These protocols prevent an O(N x M) explosion of code that have to solve for many cases. For example, since JSON is an almost ubiquitous format for wire transfer (although other things do exist like protobufs), if I had N data formats that I want to serialize, I only need to write N serializers/deserializers (SerDes). If there was no such narrow waist and there were M alternatives to JSON in wide usage, I would... Source: over 2 years ago
View more

What are some alternatives?

When comparing Apache Thrift and Protobuf, you can also consider the following products

Docker Hub - Docker Hub is a cloud-based registry service

gRPC - Application and Data, Languages & Frameworks, Remote Procedure Call (RPC), and Service Discovery

Eureka - Eureka is a contact center and enterprise performance through speech analytics that immediately reveals insights from automated analysis of communications including calls, chat, email, texts, social media, surveys and more.

Messagepack - An efficient binary serialization format.

Traefik - Load Balancer / Reverse Proxy

JSON - (JavaScript Object Notation) is a lightweight data-interchange format