YAML vs JSON vs TOML: Complete Configuration Format Comparison
YAML vs JSON vs TOML: Complete Configuration Format Comparison
Choosing the right configuration format can significantly impact your development workflow. This comprehensive guide compares YAML, JSON, and TOML to help you make the best choice for your project.
Quick Comparison Table
| Feature | JSON | YAML | TOML |
|---|---|---|---|
| Readability | Good | Excellent | Excellent |
| Comments | β No | β Yes | β Yes |
| Multi-line Strings | Escaped | β Native | β Native |
| Learning Curve | Easy | Medium | Easy |
| Browser Support | β Native | β Library | β Library |
| Type Safety | Good | Limited | Strong |
| Use Case | APIs, Data | Config Files | Config Files |
| File Size | Small | Medium | Medium |
| Parsing Speed | Very Fast | Slower | Fast |
JSON: The Universal Data Format
Overview
JSON (JavaScript Object Notation) is the most widely used data interchange format. Itβs simple, fast, and natively supported by browsers.
JSON Example
{
"name": "My Application",
"version": "1.0.0",
"database": {
"host": "localhost",
"port": 5432,
"credentials": {
"username": "admin",
"password": "secret123"
}
},
"features": ["authentication", "logging", "caching"],
"enabled": true,
"maxConnections": 100
}
JSON Pros
β
Native Browser Support - JSON.parse() and JSON.stringify() built-in
β
Fast Parsing - Highly optimized in all languages
β
Simple Syntax - Easy to learn and understand
β
Type Safety - Clear data types (string, number, boolean, null)
β
Universal - Supported everywhere
β
Machine-Friendly - Easy for computers to parse
β
Strict Validation - Errors are caught immediately
JSON Cons
β No Comments - Canβt add explanations (use separate docs)
β No Multi-line Strings - Must use \n for newlines
β Trailing Commas - Not allowed, causes errors
β Verbose - Requires quotes everywhere
β Not Human-Friendly - Hard to read in large configs
β No Variables - Canβt reference other values
Best Use Cases for JSON
- REST APIs - Industry standard for data exchange
- Data Storage - Simple database exports
- Configuration - When comments arenβt needed
- Package Files -
package.json,composer.json - Data Transfer - Between client and server
- NoSQL Databases - MongoDB, CouchDB
- State Management - Redux, Vuex stores
JSON Tools
Validators:
- DataFmt JSON Validator - Free online tool
- JSONLint - Popular validator
- VS Code - Built-in validation
Parsers:
// JavaScript
const data = JSON.parse(jsonString);
const json = JSON.stringify(data, null, 2);
// Python
import json
data = json.loads(json_string)
json_str = json.dumps(data, indent=2)
// PHP
$data = json_decode($json_string);
$json = json_encode($data, JSON_PRETTY_PRINT);
YAML: The Human-Friendly Format
Overview
YAML (YAML Ainβt Markup Language) is designed for human readability with a clean, indentation-based syntax.
YAML Example
name: My Application
version: 1.0.0
database:
host: localhost
port: 5432
credentials:
username: admin
password: secret123
features:
- authentication
- logging
- caching
enabled: true
maxConnections: 100
# This is a comment
description: |
This is a multi-line string.
It preserves line breaks.
Perfect for long descriptions.
YAML Pros
β
Highly Readable - Clean, minimal syntax
β
Comments Support - Use # for explanations
β
Multi-line Strings - Native support with | or >
β
No Quotes Needed - For most strings
β
Anchors & Aliases - Reuse configuration blocks
β
Human-Friendly - Easy to write and edit
β
Less Verbose - No brackets or commas
YAML Cons
β Indentation Sensitive - Spaces matter (tabs not allowed)
β Complex Spec - Many features can be confusing
β Slower Parsing - More complex than JSON
β Security Issues - Can execute code if not careful
β Type Ambiguity - no can be boolean or string
β No Native Browser Support - Needs library
Best Use Cases for YAML
- Docker Compose -
docker-compose.yml - Kubernetes - Deployment configs
- CI/CD Pipelines - GitHub Actions, GitLab CI
- Application Config - Rails, Symfony
- Documentation - OpenAPI/Swagger specs
- Ansible Playbooks - Infrastructure as code
- CloudFormation - AWS templates
YAML Gotchas
Problem 1: Norway Problem
# β This becomes boolean false!
country: NO
# β
Quote it
country: "NO"
Problem 2: Indentation
# β Mixed indentation breaks
settings:
debug: true
log: true # Wrong indent level
# β
Consistent spacing
settings:
debug: true
log: true
Problem 3: Multi-line Strings
# Preserves newlines
description: |
Line 1
Line 2
# Folds into single line
description: >
This is a very long
sentence that will be
folded into one line.
YAML Anchors Example
defaults: &defaults
timeout: 30
retries: 3
production:
<<: *defaults
host: prod.example.com
development:
<<: *defaults
host: localhost
timeout: 60 # Override default
TOML: The Clear Configuration Format
Overview
TOML (Tomβs Obvious, Minimal Language) is designed to be easy to read and unambiguous, focusing on configuration files.
TOML Example
name = "My Application"
version = "1.0.0"
enabled = true
maxConnections = 100
# This is a comment
[database]
host = "localhost"
port = 5432
[database.credentials]
username = "admin"
password = "secret123"
features = ["authentication", "logging", "caching"]
# Multi-line strings
description = """
This is a multi-line string.
It preserves line breaks.
Perfect for long descriptions.
"""
# Tables
[[servers]]
name = "alpha"
ip = "10.0.0.1"
[[servers]]
name = "beta"
ip = "10.0.0.2"
TOML Pros
β
Unambiguous - Clear data types, no confusion
β
Comments Support - Use # for documentation
β
Multi-line Strings - Triple quotes """
β
Easy to Read - Clean key = value format
β
Type Safety - Explicit types (dates, integers, floats)
β
No Indentation Issues - Uses sections [table]
β
Fast Parsing - Simpler than YAML
TOML Cons
β Less Known - Smaller ecosystem
β Verbose for Nested Data - Need [section.subsection]
β No Native Browser Support - Needs library
β Arrays of Tables - Can be confusing
β Limited Tool Support - Compared to JSON/YAML
β Not for Data Exchange - Mainly for config
Best Use Cases for TOML
- Rust Projects -
Cargo.toml - Python Projects -
pyproject.toml - Config Files - Application settings
- Package Managers - Cargo, Poetry
- Static Site Generators - Hugo
- Version Control -
.gitconfig
TOML Data Types
# String
name = "John"
multiline = """
Multiple
lines
"""
# Integer
age = 30
hex = 0xDEADBEEF
oct = 0o755
bin = 0b11010110
# Float
pi = 3.14159
scientific = 5e+22
# Boolean
enabled = true
disabled = false
# Date/Time
date = 2025-11-10
datetime = 2025-11-10T07:32:00Z
# Array
simple = [1, 2, 3]
mixed = ["red", "blue"]
# Inline Table
point = { x = 1, y = 2 }
Side-by-Side Comparison
Same Data in All Three Formats
JSON:
{
"server": {
"host": "localhost",
"ports": [8080, 8081, 8082],
"ssl": true
},
"database": {
"connections": 100
}
}
YAML:
server:
host: localhost
ports:
- 8080
- 8081
- 8082
ssl: true
database:
connections: 100
TOML:
[server]
host = "localhost"
ports = [8080, 8081, 8082]
ssl = true
[database]
connections = 100
Which Format Should You Choose?
Choose JSON When
β
You need browser compatibility
β
Building REST APIs
β
Speed is critical
β
Working with JavaScript
β
Data interchange between systems
β
Simple data structures
β
Donβt need comments
Choose YAML When
β
Human readability is priority
β
Complex nested configurations
β
Need comments for documentation
β
Working with Docker/Kubernetes
β
CI/CD pipeline configurations
β
Multi-line strings common
β
Team is familiar with YAML
Choose TOML When
β
Clear, unambiguous config files
β
Rust or Python projects
β
Need strong type safety
β
Want simple syntax
β
Comments are important
β
Avoid indentation issues
β
Configuration over data exchange
Performance Comparison
Parsing Speed (relative):
- JSON - Fastest (1x baseline)
- TOML - Fast (1.5-2x slower)
- YAML - Slowest (3-5x slower)
File Size (same data):
- JSON - Smallest (100% baseline)
- TOML - Medium (110-120%)
- YAML - Largest (120-130%)
Note: Differences are negligible for config files but matter for large-scale data processing.
Conversion Between Formats
JSON β YAML
Using yq (YAML processor):
# JSON to YAML
yq -P '.' data.json > data.yaml
# YAML to JSON
yq -o=json '.' data.yaml > data.json
Using Python:
import json
import yaml
# JSON to YAML
with open('data.json') as f:
data = json.load(f)
with open('data.yaml', 'w') as f:
yaml.dump(data, f)
# YAML to JSON
with open('data.yaml') as f:
data = yaml.safe_load(f)
with open('data.json', 'w') as f:
json.dump(data, f, indent=2)
JSON β TOML
Using Python:
import json
import toml
# JSON to TOML
with open('data.json') as f:
data = json.load(f)
with open('data.toml', 'w') as f:
toml.dump(data, f)
# TOML to JSON
with open('data.toml') as f:
data = toml.load(f)
with open('data.json', 'w') as f:
json.dump(data, f, indent=2)
Common Patterns
Environment-Specific Configuration
JSON:
{
"development": { "debug": true },
"production": { "debug": false }
}
YAML:
development:
debug: true
production:
debug: false
TOML:
[development]
debug = true
[production]
debug = false
Lists and Arrays
JSON:
{
"items": [
{ "name": "Item 1", "value": 10 },
{ "name": "Item 2", "value": 20 }
]
}
YAML:
items:
- name: Item 1
value: 10
- name: Item 2
value: 20
TOML:
[[items]]
name = "Item 1"
value = 10
[[items]]
name = "Item 2"
value = 20
Try Our Format Tools
Need to work with these formats? Try our free tools:
- JSON Validator & Formatter - Validate and beautify JSON
- YAML Validator - Check YAML syntax
- Format Converter - Convert between formats
Summary
Quick Decision Guide:
Use JSON if:
- β‘ Speed matters
- π Browser/API communication
- π Data interchange
- π¦ Universal compatibility needed
Use YAML if:
- π Human readability priority
- π³ Docker/Kubernetes configs
- π CI/CD pipelines
- π¬ Comments essential
Use TOML if:
- π¦ Rust/Python projects
- βοΈ Type safety important
- π Clear config files
- π― Avoid ambiguity
Hybrid Approach:
- Use JSON for APIs and data
- Use YAML/TOML for configuration
- Convert between formats as needed
Remember:
- All three are valid choices
- Pick based on your use case
- Be consistent within a project
- Consider your teamβs familiarity
Validate your config files now! π
Need to validate your configuration files? Try our free tools for JSON, YAML, and more!
Found this helpful? Try our free tools!
Explore Our Tools β