CSV Diff

updated 12 March 2026

Before you start

You need:

• Two CSVs — the "old" (left) and "new" (right) version of the same dataset. They should share a header row and, ideally, share most columns.
• A key column (or composite of columns) that uniquely identifies a record in both files. Usually an id, sku, email, or similar. Without a key, the tool falls back to row-text compare — see below.

The two files don't have to have the same columns or the same row order. The diff matches rows by key, then compares cells of the matched rows.

How to use it

1. Paste or drop your old CSV into the left pane.
2. Paste or drop your new CSV into the right pane.
3. Type the Key column(s) — one name (id) or comma-separated for a composite key (country, sku).
4. Click Compare.
5. Review the result below the panes. Colour legend:
   • green — row exists only in the new file (added).
   • red — row exists only in the old file (removed).
   • yellow — row exists in both, but at least one cell differs. The specific differing cells are highlighted.
6. Click Download diff for a CSV with a change_type column.

Key-column vs. row-text diff

Leave the key field empty and the tool falls back to comparing entire row strings as a set — useful when a file has no stable ID, but weaker because a single-cell change looks like a delete + add, and you lose the cell-level highlight.

Use a key whenever possible. If no column is unique on its own, combine two or three into a composite key; the result is almost always more useful.

What "changed" really means

• Comparison is string-exact. "1.0" and "1" are different. Normalise types in the source if that's noise.
• Only columns that exist in both files are compared for changes. A column added in the new file is reported as part of the "added" row context, not as a cell change for every existing row.
• If the same key appears more than once in one file, the extra copies are flagged so you can fix the source before trusting the diff.

Example

Old CSV:

id,name,city
1,Alice,Berlin
2,Bob,Paris
3,Carol,Rome

New CSV:

id,name,city
1,Alice,Berlin
2,Bob,Lyon
4,Dana,Madrid

Diff on id:

• id=1 — unchanged.
• id=2 — changed: city Paris → Lyon.
• id=3 — removed.
• id=4 — added.

Tips & common pitfalls

• Trim noisy columns first. Timestamps and "last updated" columns change on every row and drown out real diffs. Strip them or add them to a separate compare.
• Sort both files by key before download if you plan to eyeball the diff output — the tool itself doesn't need sorted input, but a sorted CSV is much easier to review.
• Big + wide files are slow because every matched row builds a string key and a per-column comparison. If you hit a wall, cut the file by column or by row with Split CSV first.
• Reordered columns are invisible to the diff — the tool lines up columns by name, not by position. If a column was renamed, it looks like "old column removed, new column added".
• Watch out for whitespace: trailing spaces in one file make the cell look "changed" even when it isn't. If the source has that problem, run the file through Dedupe CSV with trim first, or preprocess with a script.

Troubleshooting

Frequently asked questions