Comparison
JSON vs YAML: when to use each
JSON or YAML for your next config file or API? A developer-first comparison covering syntax, performance, tooling, gotchas, and real-world verdict.
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TL;DR
Use JSON for APIs and machine-to-machine data. Use YAML for human-edited config files (Kubernetes, CI, Ansible). Never use YAML where speed and strictness matter — the parser is 3–10× slower than JSON and accepts ambiguous inputs.
Option A
JSON
The web's default data format
Option B
YAML
Config-file favourite of DevOps
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Side-by-side
| Dimension | JSON | YAML |
|---|---|---|
| Primary use | APIs, data exchange | Config files, pipelines |
| Spec size | Small, strict (ECMA-404) | Large, permissive (YAML 1.2) |
| Comments | Not allowed | Fully supported (`#`) |
| Multi-line strings | Awkward (`\n` escapes) | Clean (`|` and `>`) |
| Parse speed | Very fast | 3–10× slower |
| Data types | string, number, bool, null, array, object | All of JSON + dates, anchors, custom tags |
| Editor support | Universal | Universal, but indent-sensitive |
| Error messages | Clear (line/column) | Often misleading (indent guessing) |
| Secrets / security | Safe to parse untrusted input | Unsafe without `safe_load` (code exec in old libs) |
| File extension | .json | .yaml / .yml |
When JSON wins
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When YAML wins
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The gotchas nobody tells you about YAML
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Performance: the numbers
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What about TOML, HCL, or JSONC?
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Frequently asked questions
Is YAML a superset of JSON?
YAML 1.2 is officially a superset — any valid JSON document is valid YAML. In practice, some YAML parsers still choke on JSON-style flow syntax for large documents, so don't rely on this for tooling.
Should I use YAML for an API?
No. Even if both ends could parse it, JSON's speed advantage and strict grammar are worth it. Every mainstream HTTP library defaults to JSON serialization anyway.
Which is easier to diff in Git?
YAML, by a wide margin. Adding one field produces a single-line diff in YAML; in JSON the trailing comma or brace placement often causes multi-line noise.
Is YAML secure?
YAML is data; the risk is in the parser. Python's PyYAML `load` (without `safe_`) can instantiate arbitrary classes — a remote code execution primitive if you parse untrusted input. Always use `safe_load` / `safeLoad`.
