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JSON Diff Checker

Compare two JSON objects and see exactly what changed. Find added, removed, and modified fields with before/after values at every nesting level.

Original

json
loading editor…

Paste the original JSON here…
or drop a file anywhere in this pane

Modified

json
loading editor…

Paste the modified JSON here…
or drop a file anywhere in this pane

Differences

json

Added, removed and changed fields will be listed here…
press to compare

What Is JSON Diff?

JSON diff (or JSON comparison) is the process of comparing two JSON objects to identify what has changed between them. The tool highlights additions, removals, and modifications at every nested level.

JSON diff checking is essential for:

  • API Debugging: Comparing expected vs actual API responses.
  • Code Review: Seeing what changed in configuration files.
  • Data Migration: Verifying data transformations.
  • Regression Testing: Ensuring changes don't break existing behavior.

How to Compare JSON Online

  1. Paste JSON A: Paste the first JSON version into the left editor.
  2. Paste JSON B: Paste the second JSON version into the right editor.
  3. Click Compare: Click the "Compare" button to see differences highlighted.
  4. Review Changes: Added fields, removed fields, and modified values are clearly labeled.

Frequently Asked Questions

What types of changes are detected?

The diff checker detects added fields, removed fields, modified values, and changed data types at any nesting level. The output provides a detailed path-based change report.

Can I diff large JSON files?

Yes. The comparison runs in your browser and handles large objects limited only by your device memory. Files up to several megabytes work well.

Is this tool safe?

Absolutely. This tool operates 100% client-side. Your JSON data never leaves your browser and is processed locally. We do not store, track, or upload your data to any server.

Real-World Examples

JSON diffing is essential when reviewing API contract changes between versions, debugging why a configuration update broke a deployment, tracking data migration accuracy, and verifying that a transformation pipeline produced the expected output.

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