JSON, XML, YAML, TOML, CSV, and Logs Compared

Structured data formats are the backbone of modern software. Each format has distinct characteristics that make it suitable for different tasks. This guide compares the six formats that Filelume supports.

Format overview

Format	Type	Human-readable	Hierarchy	Comments	Schema
JSON	Text	Moderate	Yes	No	JSON Schema
XML	Text	Moderate	Yes	Yes	XSD, DTD
YAML	Text	High	Yes	Yes	JSON Schema
TOML	Text	High	Yes	Yes	None standard
CSV	Text	Low	No (flat)	No	None
Log	Text	Moderate	No	No	None

JSON

JSON (JavaScript Object Notation) is the standard for web APIs. It is strict, widely supported, and maps directly to data structures in most programming languages.

Strengths: Universal support, fast parsing, compact syntax. Weaknesses: No comments, no multi-line strings, trailing comma errors. Best for: API responses, data interchange, configuration in web projects.

XML

XML (Extensible Markup Language) is the oldest format on this list. It is verbose but powerful, with mature tooling for validation and transformation.

Strongnesses: Schema validation, namespaces, mature tooling. Weaknesses: Verbose syntax, complex specification, slow parsing. Best for: Document formats, enterprise data exchange, configuration in legacy systems.

YAML

YAML (YAML Ain't Markup Language) prioritizes human readability. It is the dominant format for configuration in modern DevOps tools.

Strengths: Excellent readability, comments, anchors/aliases, multi-document. Weaknesses: Indentation sensitivity, slower parsing, ambiguous type coercion. Best for: CI/CD pipelines, application configuration, Kubernetes manifests.

TOML

TOML (Tom's Obvious, Minimal Language) aims to be obvious and unambiguous. It is popular in the Rust ecosystem and Python packaging.

Strengths: Obvious syntax, formal spec, type-aware, no indentation ambiguity. Weaknesses: Less widely known, verbose for deep nesting, smaller ecosystem. Best for: Project configuration, package manifests, settings files.

CSV

CSV (Comma-Separated Values) is the simplest tabular format. It is universal for flat data exchange.

Strengths: Universal support, compact, easy to generate. Weaknesses: No standard encoding, no data type information, no hierarchy. Best for: Spreadsheet data, database exports, simple datasets.

Log files

Log files are semi-structured text records. They vary widely in format but generally contain timestamps, severity levels, and messages.

Strengths: Chronological record, machine and human parseable. Weaknesses: No universal format, inconsistent structure, large file sizes. Best for: Debugging, monitoring, incident response, audit trails.

Choosing the right format

The right format depends on your use case:

API communication: JSON
Human-edited configuration: YAML or TOML
Enterprise data exchange: XML
Tabular data: CSV
System events: Log files
Documentation: Markdown

Viewing all formats

Filelume supports all six formats plus Markdown. Each format gets an appropriate viewer:

Markdown, JSON, XML, YAML, TOML: Dual-pane workspace with Original and Rendered views.
CSV: Direct table view with search, filters, and sorting.
Log: Direct event viewer with level filters and timeline.

All processing happens locally in your browser. No upload, no account, no server.

Start exploring

Choose a viewer from the Tools menu and load a file. The content stays on your device, and you can switch between views, apply filters, and export results as needed.