YAML vs JSON: What’s the Difference?

As a developer, you’ve probably already watched a couple of YouTube videos or read some articles that mention YAML, JSON, or both. These two data serialization formats are widely used in the tech industry for storage, configuration, and exchanging data between different systems and programming languages.

However, if you’re a budding developer or new to programming, it’s likely you got stumped at the parts where these two were mentioned.

That’s why we’ve put together this detailed article, shedding light on the differences between YAML and JSON to make things clearer for you. But, first, what do the acronyms even stand for?

YAML vs JSON: What Exactly Are They?

YAML, short for “YAML Ain’t Markup Language” or “Yet Another Markup Language,” according to some quarters, is a versatile and expressive data format used for data serialization format. It aims to strike a balance between being easily readable by humans and being easily parseable by machines.

Its syntax allows for a more relaxed and expressive representation of data, utilizing indentation and whitespace. YAML files often resemble structured documents and have become a favorite among developers for configuration files.

On the flip side, JSON, or “JavaScript Object Notation,” is a massively popular, efficient, and lightweight data interchange format. Inspired by JavaScript object literals, JSON features a very simple and concise syntax that focuses on data and key-value pairs.

It has become the de facto standard for web APIs due to its ease of use and compatibility with multiple programming languages. Now that we’ve got an idea of what they are, let’s pit YAML vs JSON side-by-side and try to understand the intricacies of each format.

YAML vs JSON: Side-by-Side Comparison

JSON vs YAML: What’s the Difference?

Understanding these distinctions can help you determine which format is used in a particular case and not the other. Let’s delve into the main differences between them.

Syntax and Readability

YAML uses indentation and whitespace to structure data, as earlier mentioned. This makes it more readable and akin to a document, which can be helpful for humans who are trying to understand the data. To put it in perspective, let’s suppose you’re arranging a shopping list. In YAML, you’d list your items with spaces, creating a representation as such:

fruits:
  - apple
  - banana
  - orange

This is pretty likely how you would jot the list on a piece of paper. In YAML, the indentation helps to show the hierarchy of the data, and the spacing makes it easy to scan the code.

JSON, meanwhile, uses braces and commas to define its structure. This makes it more compact and easily machine-readable. We would represent our previous list as such in JSON:

{
  "fruits": ["apple", "banana", "orange"]
}

The braces and commas make it clear how the data is structured, and the lack of whitespace makes it a bit easier for programs to parse.

Generally, the design goal of JSON is to be as simple as possible and universally usable, which reduces the readability of the data to some extent.

In contrast, the design goal of YAML is to provide a good human-readable format and support for serializing arbitrary native data structures. 

Comments

Closely related to syntax and readability, commenting is another area in which these two take different approaches. YAML’s flexibility allows you to add comments, making it easier to read and understand by including helpful tips and explanations in the code.

ingredients:
  - flour  # Don't forget to sift it for a smoother texture!
  - sugar  # A little extra sweetness never hurt anyone
  - eggs   # Remember to beat them until fluffy

YAML even allows multiline comments:

# This is a multi-line comment in YAML
# You can use as many lines as you need
# To explain what each section of your code does

On the flip side, JSON doesn’t provide a way to add comments, choosing to keep everything clean and concise. You would have to take your time to understand complex data represented in JSON format.

Order

In JSON, the order of elements is not really important. This means that you can rearrange the elements in any order and the JSON will still be valid. This can be helpful for flexibility, as you can change the order of the elements without having to change the code that parses the JSON.

However, it can also make it more difficult to discern the structure of the JSON at a glance as the order of the elements is not a reliable indicator of the structure of the data.

In YAML, on the other hand, the order of elements matters, creating a consistent and predictable structure. YAML files are, therefore, more consistent, but it can also make them more difficult to change.

It’s this consistency that lends YAML files inherent clarity, allowing developers to comprehend the structure effortlessly. 

While YAML’s emphasis on order brings consistency, altering the order of elements in a YAML file can be a tad bit trickier and challenging. You can’t simply shuffle elements around without affecting the structure and integrity of the file.

Inline Referencing

YAML allows for inline referencing, which can be useful for reducing duplication in your code. For example, you can define a variable in one place and then reference it elsewhere in your code.

JSON does not support inline referencing. Here is an example of inline referencing in YAML:

people:
- name: John Doe
  age: 30
  favorite_color: &color blue
- name: Jane Doe
  age: 25
  favorite_color: *color

In this example, the variable color is defined once and then referenced twice. This can help to reduce duplication in your code and make it easier to maintain.

Here is one way you would represent the above data in JSON:

{
  "people": [
    {
      "name": "John Doe",
      "age": 30,
      "favorite_color": "blue"
    },
    {
      "name": "Jane Doe",
      "age": 25,
      "favorite_color": "blue"
    }
  ]
}

Here, the value of the favorite_color property is repeated twice as inline referencing isn’t supported. This duplication makes such JSON data more difficult to read and maintain.

Extensibility

As far as extensibility goes, JSON is not extensible. This means that you cannot add new properties or types to JSON data in a straightforward way. If you need to add new data to JSON, you’d need to create a new JSON object.

This is inconvenient if you need to add new data to existing JSON files. YAML allows you to add new properties and types to YAML data. This really helps when you need to add new data to existing YAML files.

Programming Language Support

JSON enjoys widespread adoption and support across various programming languages. This is because JSON is a subset of the ubiquitous JavaScript. JSON’s wide adoption in web development gives it an advantage in terms of available resources and community support.

YAML is also versatile and has ready support in developer circles. YAML parsers are available for a wide range of languages, including Python, Ruby, Java, and many more. 

However, JSON’s simplicity and straightforwardness make it easy to integrate with a plethora of programming languages, including Python, C++, PHP, and more besides JavaScript. It’s a language-agnostic companion that seamlessly fits into diverse coding ecosystems.

Both YAML and JSON provide libraries and tools that simplify working with their respective formats in different programming languages. From serialization and deserialization to validation and manipulation, you’ll find robust support and libraries tailored to your programming needs.

In short, JSON’s popularity and ubiquity in web development give it a slight edge in terms of available resources and community support. Its compatibility with JavaScript, the lingua franca of the web, makes it a natural choice for web-related projects.

Applications

YAML and JSON find application in different use cases. Let’s have a closer look at some of them.

JSON

JSON shines in several areas due to its simplicity and compatibility. It’s widely used in web development, where it serves as the go-to format for transmitting data between the server side and client side.

With its lightweight structure and easy-to-read syntax, JSON effortlessly facilitates data exchange, making it ideal for APIs. It’s essentially the backbone of many popular web services, such as social media, enabling seamless communication between different systems.

JSON is also extensively employed in configuration files. Its straightforward nature makes it perfect for defining settings and parameters in software applications, including package managers like NPM and Composer. 

Firebase and other document-based databases rely on it for data exchange. Additionally, it finds its place in configuring tools like VS Code, allowing developers to specify database connections, application preferences, and system configurations effortlessly.

YAML

YAML is best suited for scenarios that demand a data representation that is both user-friendly and expressive. Its remarkable strength lies in configuration files, where it stands out as a potent resource for defining intricate structures.

Its readability and ability to handle nested data structures make YAML an exceptional choice for configuration management, especially in projects that involve complex setups or intricate orchestration.

It finds utility in scripting and automation in defining workflows, automating tasks, and serializing data. Its clean and intuitive syntax, characterized by indentation and dashes, fosters easy comprehension and maintenance of scripts.

Consequently, YAML emerges as the preferred format for powerful tools like Ansible, where it acts as a declarative language for precisely describing infrastructure as code.

This flexibility and versatility extend to popular technologies such as Docker, Flutter, and Google Cloud. YAML’s user-friendly nature and support for complex structures make it an ideal choice for configuring Docker containers, enabling developers to define containerized environments effortlessly.

Similarly, in the context of Flutter, YAML empowers developers to specify project configurations and dependencies seamlessly. Google Cloud leverages YAML for defining infrastructure setups, orchestrating resources, and streamlining deployment processes.

YAML vs JSON: 7 Must-Know Facts

1. YAML was first introduced in 2001 by Clark Evans, Ingy döt Net, and Oren Ben-Kiki as an attempt to create a more human-friendly alternative to XML.
2. Douglas Crockford, the creator of JSON, originally developed the format in 2001 as a way to store and transmit data between web applications and web servers. However, it wasn’t until 2002 that JSON was released to the public as an open standard.
3. YAML and JSON are both language-agnostic and can be used with any programming language that supports their respective parsers and serializers.
4. While YAML is often used for configuration files and data exchange, JSON is widely adopted for web APIs and data transmission between client and server.
5. YAML is a superset of JSON, meaning that any valid JSON code can, at least in theory, be parsed by a YAML compiler.
6. YAML supports more complex data structures like lists and associative arrays, while JSON cannot handle them.
7. JSON is more compact than YAML, making it faster to parse and better for machine-to-machine communication hence the use in web APIs.

Now that we’ve looked at both in sufficient detail, you might be getting started on a new project and wondering which format to go by. Here are some pointers.

YAML vs JSON: Which One Is Better? Which One Should I Choose for My Project?

Your choice here will largely be in the context of using either YAML or JSON for data serialization vis-à-vis data exchange. That’s because, basically, JSON is best employed in web development and data exchange scenarios, whereas YAML finds its place in configuration files and complex data representation.

JSON’s lightweight and compatibility make it a common choice for APIs, while YAML’s readability and expressiveness make it a top contender for configuration management, scripting, and automation tasks.

YAML is clearly out of the question if you’re starting a project that heavily relies on JSON-based technologies like Firebase. Its wide-ranging applications span prominent technologies like Docker and Kubernetes, enabling developers to streamline their workflows and achieve efficient and reliable results.

With these differences in mind and of course aligning your choice with the specific technologies and frameworks you’re working on within your project, you should now be in a better position to pick one over the other.