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What is JSON?

JavaScript Object Notation is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language.
JSON is a tool in the Languages category of a tech stack.

Who uses JSON?

152 companies reportedly use JSON in their tech stacks, including doubleSlash, Biting Bit, and Trade Republic.

1693 developers on StackShare have stated that they use JSON.

JSON Integrations

JavaScript, MySQL, PostgreSQL, MongoDB, and TimescaleDB are some of the popular tools that integrate with JSON. Here's a list of all 72 tools that integrate with JSON.
Pros of JSON
Widely supported
Decisions about JSON

Here are some stack decisions, common use cases and reviews by companies and developers who chose JSON in their tech stack.

Lukas Varkalis
Needs advice

Hi all,

I need advice for object-oriented data analysis. I have exported a collection of users from Firebase to JSON, and I want to analyze it, for example, how many users are females, males, etc. Are there any tools or packages that could help me quickly analyze this data?

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Subrat Das
Lead Enginner at HCL Technologies LTD · | 2 upvotes · 39.2K views
Needs advice
Karate DSLKarate DSLMongoDBMongoDB

I want to develop a custom API testing tool for which I have chosen Karate DSL. As I will be dealing with APIs, I need to handle lots of data in JSON or XML format. I need advice on which DB is best suited for my application. MongoDB or MySQL?

Please Suggest. Thank you in advance.

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Needs advice

Hi. Currently, I have a requirement where I have to create a new JSON file based on the input CSV file, validate the generated JSON file, and upload the JSON file into the application (which runs in AWS) using API. Kindly suggest the best language that can meet the above requirement. I feel Python will be better, but I am not sure with the justification of why python. Can you provide your views on this?

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Needs advice

Hi all, I am trying to decide on a database for time-series data. The data could be tracking some simple series like statistics over time or could be a nested JSON (multi-level nested). I have been experimenting with InfluxDB for the former case of a simple list of variables over time. The continuous queries are powerful too. But for the latter case, where InfluxDB requires to flatten out a nested JSON before saving it into the database the complexity arises. The nested JSON could be objects or a list of objects and objects under objects in which a complete flattening doesn't leave the data in a state for the queries I'm thinking.

  { "timestamp": "2021-09-06T12:51:00Z",
    "name": "Name1",
    "books": [
        { "title": "Book1", "page": 100 },
        { "title": "Book2", "page": 280 },
 { "timestamp": "2021-09-06T12:52:00Z",
   "name": "Name2",
   "books": [
       { "title": "Book1", "page": 320},
       { "title": "Book2", "page": 530 },
       { "title": "Book3", "page": 150 },

Sample query: With a time range, for name xyz, find all the book title for which # of page < 400.

If I flatten it completely, it will result in fields like books_0_title, books_0_page, books_1_title, books_1_page, ... And by losing the nested context it will be hard to return one field (title) where some condition for another field (page) satisfies.

Appreciate any suggestions. Even a piece of generic advice on handling the time-series and choosing the database is welcome!

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Needs advice
GitHub EnterpriseGitHub Enterprise

Can I create reusable ARM templates (JSON files) in the Bit community? I see examples of components made from React codes. How can I make the same using JSON files?

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Needs advice

Searching for a tool (library?) to build a big document browser/search, something like a bible browser with selecting chapters and paragraphs. Navigation should be tree-based, and searching in files (the content is split into several JSON) would be a nice addition. Searching can be server-side (i.e., PHP) with JavaScript frontend for AJAX loading. Can someone point me in the right direction?

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Blog Posts

Aug 28 2019 at 3:10AM


PythonJavaAmazon S3+16

JSON Alternatives & Comparisons

What are some alternatives to JSON?
A human-readable data-serialization language. It is commonly used for configuration files, but could be used in many applications where data is being stored or transmitted.
Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.
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.
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
It is an ISO/IEC approved, OASIS standard that defines a set of best practices for building and consuming RESTful APIs. It helps you focus on your business logic while building RESTful APIs without having to worry about the various approaches to define request and response headers, status codes, HTTP methods, URL conventions, media types, payload formats, query options, etc.
See all alternatives

JSON's Followers
1570 developers follow JSON to keep up with related blogs and decisions.