Difference between YAML and JSON

Modern software development places more emphasis on configuration management and data serialization formats. Among various data formats used, YAML and JSON have become especially popular among API communication, DevOps, backend engineering, and infrastructure-as-code (IaC) workflows.

Key Takeaways:
  • YAML and JSON serve similar purposes, but they differ significantly in design philosophy, ease of use, readability, flexibility, and tooling support.
  • YAML is a better fit depending on several factors, like data type, data storage, or data transfer formats. But JSON’s popularity is an advantage.
  • Understanding the differences between YAML and JSON can help developers choose the right format for their specific use.
  • Both YAML and JSON are popular formats, and knowing the key differences between them is vital for making informed decisions and unleashing the full potential of your applications.

This article explored the key differences between YAML and JSON, covering their history, syntax, data structures, usability, tooling, performance, security considerations, and real-world examples.

What is YAML?

YAML (YAML Ain’t Markup Language) is a human-readable data serialization language created in 2001. YAML prioritizes readability and convenience for humans, making it a suitable language for configuration files, infrastructure definitions, and complex multi-document structures.

YAML is readable, adaptable, and flexible, which makes it a popular choice for various applications. YAML offers additional features compared to JSON, such as comments and anchors.

Its core design goals of YAML include:
  • High readability
  • Support for complex data models
  • Flexibility
  • Extensibility
Here is the standard YAML file:
title: The Great War
author: Diana Scott
year: 1952
genre:
  - Fiction
  - Classic
publisher:
  name: Scribe
  location: New York

As shown in the above code, a typical YAML file comprises various building blocks, including indentation, key-value pairs, nested structures, scalar values, and lists.

YAML is frequently used in the following applications:
  • Kubernetes configuration files
  • Ansible playbooks
  • GitHub Actions workflows
  • Docker Compose files
  • CI/CD pipelines

YAML is often considered more expressive but also more error-prone than JSON because of its overdependence on indentation.

What is JSON?

JSON stands for JavaScript Object Notation and is a lightweight, open-standard data-interchange format derived from JavaScript object syntax. It was introduced in the early 2000s as a simpler alternative to XML for web APIs and data storage. JSON is a stateless paradigm that performs real-time server-to-browser communication and does not rely heavily on plugins like Java and Flash.

With its lightweight and secure solutions, JSON is widely supported across programming languages and has become the de facto standard for representing structured data in web services, configuration files, logs, and NoSQL databases, such as MongoDB.

The following code shows an example of a JSON structure:
{
  "name": "Mary An",
  "age": 27,
  "email": "maryA@example.com",
  "address": {
    "street": "123 Main St",
    "city": "New York",
    "state": "NY",
    "postalCode": "10001"
  },
  "hobbies": ["reading", "coding", "playing"],
  "isEmployed": true
}

As shown in the above code, JSON is a subset of JavaScript and employs a simple syntax based on attribute-value pairs. Attributes are defined as keys (such as name, age, etc.) followed by a colon (:), and their corresponding values.

JSON supports various data types, including numbers, strings, booleans, arrays, and objects.

JSON’s primary goals are:
  • Simplicity
  • Machine friendliness
  • Consistency
  • Language independence
An example JSON structure is shown here:
{
  "name": "John Doe",
  "age": 30,
  "email": "johndoe@example.com",
  "address": {
    "street": "123 Main St",
    "city": "New York",
    "state": "NY",
    "postalCode": "10001"
  },
  "hobbies": ["reading", "coding", "playing guitar"],
  "isEmployed": true
}

Because JSON maps directly to JavaScript objects, it is extensively used in front-end development, REST APIs, and event-driven systems.

Similarities between YAML and JSON

YAML and JSON share a few similarities. Let’s discuss them here:

Human Readability

  • YAML: YAML features a more relaxed and flexible syntax designed for human readability. It has a natural language-like format and uses indentation and whitespace for structure.
  • JSON: JSON has a relatively compact syntax, using braces {} for objects and brackets [] for arrays. While JSON is human-readable like YAML, its structure can become nested and more complex to understand as data complexity increases.

Data Interchange

  • YAML: YAML is a data interchange format and can be parsed and processed by various programming languages. It contains libraries to handle YAML data in most programming languages.
  • JSON: JSON is widely used for data interchange between systems and APIs and has built-in support in most programming languages. It makes it easy to parse and generate JSON data. As JSON’s structure closely aligns with the object notation of many programming languages, it is a popular choice for data serialization.

Support for Data Types

  • YAML: YAML supports data types, including strings, numbers, booleans, null, arrays, and objects. It also supports advanced data types, such as dates, timestamps, and complex data structures. Developers can represent data more accurately using these datatypes and express hierarchical relationships more naturally.
  • JSON: JSON supports similar data types as YAML, including strings, numbers, booleans, null, arrays, and objects. It has a straightforward way to represent structured data and is widely used for storing and transmitting data in web applications.

Differences between YAML and JSON

YAML and JSON have notable differences between them, as discussed below:

YAML & JSON – Syntax Comparison

Syntax is one of the most notable and impactful differences between YAML and JSON. Below are two simple syntax examples in YAML and JSON:

YAML Example JSON Example 
name: John Right
age: 32
isAdmin: false
skills:
  - Python
  - Perl
address:
  city: New York
  zip: 94103
			
{
  "name": "John Right",
  "age": 32,
  "isAdmin": false,
  "skills": ["Python", "Perl"],
  "address": {
    "city": "New York",
    "zip": 94103
  }
}

As seen in the examples, in YAML, indentation defines hierarchy, while JSON relies on curly braces {}, brackets [], commas, and colons. This makes YAML visually cleaner and more readable, but also easier to break due to indentation errors.

Data Types and Structures

Both formats, YAML and JSON, support similar primitive and complex data types but differ in how they represent them. For example,

YAML supports the following types:
  • Multi-document streams
  • Anchors & references (& and *)
  • Complex keys
  • Custom tags
  • Multi-line strings
  • Arbitrary precision numbers
  • Timestamps
JSON supports:
  • Strings
  • Numbers
  • Booleans
  • Arrays
  • Objects (key-value maps)
  • Null

As shown, YAML supports all the types supported by JSON, in addition to more features such as anchors, aliases, and multi-line strings. JSON, however, has no direct equivalent to anchors or references.

Human Readability

YAML: Highly Readable

YAML design emphasizes human readability. It supports clear indentation, comments, and multi-line formatting and avoids punctuation clutter. These distinguishing features make YAML excellent for configuration-heavy applications where readability is essential.

However, when indentation is inconsistent or ambiguous, the same flexibility can cause errors.

JSON: Readable but Verbose

JSON is more verbose and rigid than YAML. It uses brackets and braces, which can make code cluttered, especially in large JSON documents.

However, JSON is strict and reduces ambiguity, thereby improving machine reliability.

Comments Support

This is one of the most significant usability differences between YAML and JSON. YAML supports comments, whereas JSON does not (according to the official specifications). While some JSON implementations allow comments, they are non-standard.

Comments are represented in YAML as shown here:
 # This is a comment in YAML
name: John Doe

Use Cases and Application Areas

YAML: YAML is used in applications when humans frequently edit, read, and maintain the configuration.

YAML is a guaranteed choice for:
  • Declarative configuration files
  • Infrastructure as Code (IaC)
  • CI/CD workflows
  • Container/orchestration tools like Docker
  • Complex hierarchical configurations
Examples of systems using YAML extensively are:
  • Kubernetes
  • GitHub Actions
  • AWS CloudFormation (supports YAML/JSON)
  • Docker Compose
  • Ansible

JSON: JSON is simple and provides universal support, making it a natural choice when machine interoperability and performance are key considerations.

JSON is ideal for:
  • REST APIs
  • Web applications
  • Data interchange between services
  • Logging formats
  • Settings in web apps and libraries
  • NoSQL database documents

Tooling and Ecosystem Support

  • YAML Tools: YAML has strong tooling. YAML parsers are available for Python, Ruby, Go, Java, and many other languages.
    Popular YAML-based ecosystems are:
    • Kubernetes YAML files
    • GitLab CI
    • GitHub Actions
    • Ansible
    • Helm charts
  • JSON Tools: JSON’s tooling ecosystem is much broader and is supported everywhere from browsers to embedded systems. Libraries exist for major languages such as Python, Java, C#, Go, and JavaScript.
    Popular JSON-based technologies are:
    • REST APIs
    • OpenAPI/Swagger
    • GraphQL responses
    • Elasticsearch
    • MongoDB

Performance Comparison

YAML:

YAML parsing is slower as the parser has to handle:
  • Complex syntax
  • Multi-line structures
  • Tags
  • Anchors
  • Indentation semantics

JSON:

JSON, on the other hand, is generally faster to parse and generate due to its simplicity and limited feature set.

According to performance studies, YAML parsing is up to 10x slower than JSON for large datasets.

Security Considerations

YAML Security:

YAML’s complexity introduces several security concerns. Some YAML parsers support such features that can lead to:
  • Arbitrary code execution
  • Remote file inclusion
  • Object deserialization vulnerabilities

More security risks are introduced when languages that use YAML are involved. For example, in languages like Ruby or Python, unsafe loaders can create objects during parsing, a practice that is inherently dangerous.

Developers must use safe loaders (e.g., yaml.safe_load in Python) to overcome this situation.

JSON Security:

JSON is simpler, reducing the attack surface. Its native data types map cleanly to their corresponding data types in most programming languages, minimizing risk and making it safer than YAML.

Strictness and Validation

YAML:

YAML is a flexible data format. However, this flexibility comes with pitfalls:
  • Tabs vs spaces issues in indentation.
  • Ambiguous strings (e.g., "yes", "no", "on", "off") are interpreted as booleans.
  • Indentation mistakes can break the entire file.

These reasons prompt YAML to use linting tools to maintain quality.

JSON:

JSON syntax is stricter than YAML:
  • It requires quotes around keys.
  • JSON prohibits trailing commas.
  • It doesn’t allow comments.
  • JSON has a strict standard (ECMA-404)

This strictness ensures consistency and reduces the likelihood of developer errors.

Learning Curve

YAML:

YAML has a steeper learning curve primarily due to its powerful features (anchors, references, tags, multi-doc files), which require more profound knowledge. Additionally, developers unfamiliar with indentation rules often make mistakes.

JSON:

JSON is comparatively easy to learn, as its syntax is similar to that of other basic programming languages. Hence, anyone familiar with JavaScript or basic programming can quickly understand JSON.

Real-World Examples

The table below displays the Kubernetes Deployment configuration in YAML and the REST API response in JSON.

YAML – Kubernetes Deployment JSON – REST API Response 
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
        - name: app
          image: myapp:latest
			
{
  "status": "success",
  "data": {
    "id": 123,
    "message": "User created successfully"
  }
}

YAML vs. JSON – Core Differences

The following table summarizes the core differences between YAML and JSON:

Feature YAML JSON
Origin Independent serialization language JavaScript
Readability Excellent Good
Complexity High Low
Comments Supported Not supported
Trailing commas Sometimes No
Multi-line strings Extensive Limited
Machine parsing Complex Easy
Human editing Excellent Good
Anchors/references Yes No
Performance Slow Fast
Security risk Higher Low
Ideal use cases Config files, IaC, CI/CD APIs, logs, data transfer

When to Use YAML vs. JSON?

The decision regarding when to use YAML or JSON depends on your specific project requirements and use case. Consider the following factors when deciding whether to use YAML or JSON.

Use Case

The nature of your data and the intended use case decide whether you should use YAML or JSON. For instance, if you are working with APIs, JSON is a natural fit as it is specifically designed for data interchange between systems and is widely used in web services.

If you are working with configuration files or documents that require excellent human readability, YAML is the best choice as it provides a more intuitive and expressive syntax.

Language Support

Next, consider the programming languages and libraries you’ll be using in your project. Almost all the major programming languages provide native support for JSON.

YAML is also well-supported but may require the use of external libraries or plugins in a few programming languages. In brief, ensure that the chosen format aligns with the programming language ecosystem and tools.

Complexity

Another factor to consider when choosing between YAML and JSON is the complexity of the data structures and the features required. While JSON is well-suited for simple data models, such as key-value pairs or arrays of values,

YAML offers data structures that involve hierarchical relationships, nested objects, or require comments and reusable references.

YAML’s indentation-based structure enables easy nesting and enhances readability for complex data.

Ecosystem and Interoperability

Consideration is to be given to the existing ecosystem and tooling available for each format. JSON has been around longer than YAML and has a mature ecosystem with extensive support in various libraries, frameworks, and tools. It is extensively used and well-documented, making it easier to find solutions and use existing resources.

YAML, although less widespread, is more popular in the DevOps and configuration management space. It has an emerging ecosystem with libraries and tools to support YAML parsing and manipulation.

Security

Security is an important aspect when working with data formats. JSON is generally considered secure, while YAML parsers are still evolving, and certain implementations may have security concerns.

So based on the factors discussed above, we have concluded the following:

Choose JSON if:

  • You are building APIs
  • Data needs to be transferred across systems.
  • Performance is critical.
  • There is a requirement for strong validation and consistency.
  • You are looking for minimal risk of formatting errors.

Choose YAML if:

  • Writing large configuration files is your primary requirement.
  • Human readability is a critical factor.
  • You need expressive features, such as anchors or multiple documents, in your file.
  • You are working with tools like Kubernetes, Ansible, or Docker Compose.

Balanced View

However, though there is a clear separation regarding when to use YAML and JSON, modern systems support both. For example:
  • CloudFormation templates use JSON or YAML.
  • GitHub Actions use YAML only.
  • Terraform utilizes HCL systems, which are similar to JSON/YAML concepts.
  • Kubernetes prefers YAML for its configuration files.

Ultimately, it depends on context and requirements to use YAML or JSON.

Future Trends

YAML dominates DevOps while JSON continues to dominate web technologies. Concepts like JSON5 and HCL aim to bridge the gap between human readability and machine simplicity.

Some developers advocate moving away from YAML due to:
  • Parsing complexity
  • Security risks
  • Indentation issues

Others argue that YAML’s readability is unmatched for configuration.

Both formats are likely to remain important for years to come.

Conclusion

YAML and JSON tend to help with similar problems. YAML is better suited for complex configuration formats, IaC, and DevOps automations due to being human-readable while still bringing a lot of features. JSON, on the other hand, is a light-weight, fast, and machine-readable representation of structured data in a textual way, which is good for the interchange of data on the internet or API messages.

Knowing the contrast between them allows developers to choose based on readability requirements, acceptability of complexity level, security implications, and performance considerations. In practice, many teams end up using both; JSON when you need some consistency and interoperability, YAML when human readability and flexibility matter more.

Shilpa Prabhudesai