JSON Data Deduplicator
Find and remove duplicate items in a JSON array. Compare whole objects (key order does not matter) or only selected keys such as email or customer.id, ignore differences in upper/lower case and extra spaces, and keep the first or the last occurrence. The result is the deduplicated array plus a list of the removed items.
- Runs in your browser
- No sign-up
- Free to use
Processed entirely in your browser – your data is not uploaded. Files up to 50 MB.
How to use JSON Data Deduplicator
- Paste a JSON array or open a file.
- Choose the keys to compare (optional).
- Choose which occurrence to keep.
- Copy or download the result.
JSON Data Deduplicator features
Key-based
Compare by one or more keys, including nested a.b.
Whole-object mode
Key order ignored.
Case and spaces
Optional normalisation.
First or last
Keep the newest record if needed.
Removed list
See what was dropped.
Private
Runs in your browser; nothing is uploaded.
When to use JSON Data Deduplicator
- Merging exports from several systems.
- Cleaning contact lists.
- De-duplicating API results.
- Preparing data for imports.
JSON Data Deduplicator FAQ
Does it change the remaining objects?
No – kept objects are output exactly as they were.
What if a key is missing?
Items without the key are compared with an empty value.
Can it handle JSON Lines?
Yes, one object per line.
Duplicates hide in details
“Anna@Example.com ” and “anna@example.com” are the same person. Normalising case and spaces before comparing finds duplicates that exact matching misses.
Private by design: your data is read and processed entirely in your browser with JavaScript. Nothing is uploaded to our server, so you can work with customer lists, exports and internal reports safely. Files up to 50 MB are supported; very large files depend on your device’s memory.
Input formats: paste or open CSV (comma, semicolon, tab or pipe – detected automatically), TSV or JSON (an array of objects, an object with a data, items or results array, or JSON Lines). The first CSV row is used as the header; JSON keys become columns, and nested values are kept as JSON text.
Missing values are recognised consistently across the data tools: empty cells and common placeholders such as NULL, N/A, NA, NaN, none, “-” and undefined. Types are inferred from the values – integer, decimal, boolean, date, email, URL, JSON or text – and columns with mixed types are flagged.
Related tools on this site cover the rest of a data workflow: the CSV cleaner, viewer, splitter and merger, converters between CSV, JSON, Excel and SQL, the JSON formatter and validator, and the other profiling, validation and statistics tools in this group.
Who it is for: analysts preparing data for a report, developers checking an API export or a database dump, marketers cleaning contact lists before an import, and students learning data quality. No account, no installation and no spreadsheet formulas are needed.