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JSON VS Apache Thrift

Compare JSON VS Apache Thrift and see what are their differences

JSON logo JSON

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

Apache Thrift logo Apache Thrift

An interface definition language and communication protocol for creating cross-language services.
  • JSON Landing page
    Landing page //
    2021-09-28
  • Apache Thrift Landing page
    Landing page //
    2019-07-12

JSON features and specs

  • Simplicity
    JSON is easy to read and write due to its straightforward syntax, making it a convenient data format for both humans and machines.
  • Language Independence
    JSON is supported by many programming languages, making it a versatile choice for data interchange across different environments.
  • Lightweight
    JSON's compact format allows for efficient data transfer, which is particularly beneficial in web applications where bandwidth is a concern.
  • Integration
    JSON easily integrates with modern web technologies and APIs, making it a preferred choice for RESTful services and web applications.
  • Data Structure
    JSON supports complex data structures, including objects and arrays, providing flexibility in representing various data forms.

Possible disadvantages of JSON

  • Limited Data Types
    JSON supports a limited set of data types, which may require additional handling when working with more complex data structures found in other formats.
  • No Comments
    JSON lacks a native mechanism for including comments within the data, which can be a limitation for documentation and readability purposes.
  • Security Concerns
    Parsing JSON can introduce security vulnerabilities if not properly handled, such as malicious data execution through insecure deserialization.
  • Verbosity
    Although lightweight, JSON can become verbose for highly nested structures, which can impact readability and processing performance.
  • Error Handling
    JSON's lack of detailed error handling mechanisms can make debugging more difficult when dealing with malformed data or parsing errors.

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.

JSON videos

Parsing JSON Review - Part 1

More videos:

  • Review - Parsing JSON Review - Part 2
  • Review - JSon Foreign Vol.1 Review

Apache Thrift videos

Apache Thrift

Category Popularity

0-100% (relative to JSON and Apache Thrift)
Developer Tools
72 72%
28% 28
Web Servers
0 0%
100% 100
Software Development
100 100%
0% 0
Web And Application Servers

User comments

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Social recommendations and mentions

Apache Thrift might be a bit more popular than JSON. We know about 13 links to it since March 2021 and only 13 links to JSON. 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.

JSON mentions (13)

  • The Last Breaking Change | JSON Schema Blog
    The YAML 0.1 spec was sent to a public user group in May 2001. JSON was named in a State Software internal discussion. State Software was founded in March 2001. json.org was launched in 2002. Therefore you’re just wrong: YAML came out before JSON. Source: about 2 years ago
  • Why does wine give warnings about using 64bit prefixes, or has 32bit packages? Hasn't the world moved on from 32 bit a century ago?
    How come that doesn't apply to other libraries? For example, when I write Java or Node.js programs, I don't need to make sure packages like json.org or express.js have a 32bit or 64bit environment. What makes windows libs different than NPM libs? Source: over 2 years ago
  • “Ignore the f'ing haters ” And other lessons learned from creating a popular
    The first two sentences of the text on http://json.org are "JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write." It's a primary goal of JSON, it's fair to question whether it's successful at it. Personally, I'd much rather write TOML or S expressions. I don't like YAML at all, the whitespace sensitivity drives me nuts. - Source: Hacker News / over 2 years ago
  • Recording your JSON data to MCAP, a file format that support multiple serialization formats
    To help you make the transition, we’ve written a tutorial on how to write an MCAP writer in Python to record JSON data to an MCAP file. Source: almost 3 years ago
  • replace \" with "
    What you need to probably do is to step back and learn the format for JSON, and the core data structures that you will find in most languages:. Source: almost 3 years ago
View more

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
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What are some alternatives?

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

LibreOffice - Base - Base, database, database frontend, LibreOffice, ODF, Open Standards, SQL, ODBC

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

Microsoft Office Access - Access is now much more than a way to create desktop databases. It’s an easy-to-use tool for quickly creating browser-based database applications.

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.

Brilliant Database - Create a personal or business desktop database fast and easily using this simple all-in-one database software. Free 30 day trial.

Traefik - Load Balancer / Reverse Proxy