CSV Join / Merge / Compare

How to use CSV Join, Merge & Compare

Reconcile two CSV exports — from CRM and billing, QA and production, source system and warehouse — using a shared key column such as id, email, order_id, or a composite key. Find missing rows on either side, detect duplicate keys, see exactly which cells changed, and export a joined CSV ready for Excel, Google Sheets, or a downstream load. All processing happens in your browser; no spreadsheet is uploaded.

What it does

• Join two CSVs by a single key or composite key.
• Support for inner, left, right, and outer (full) joins.
• Reports missing rows on each side and duplicate keys within each input.
• Cell-by-cell change detection for matched rows.
• Handles comma, semicolon, tab, and pipe delimiters; auto-detects headers and quoting.
• Exports the joined / merged CSV, the change report, and the diff summary.

When to use it

• QA vs production reconciliation by primary key.
• Compare CRM and billing exports to spot mismatched accounts.
• Validate a database migration by comparing pre- and post-cutover dumps.
• Reconcile analytics events vs server logs.
• Merge two partial exports into a single deduplicated CSV.
• Spot-check a vendor file against your internal source-of-truth export.

How to use it

1. Paste or load the left CSV and the right CSV. Headers are required for keyed comparison.
2. Select the key column (or columns for a composite key) that exists in both files.
3. Choose the join type: inner shows matches only; left and right keep one side; outer keeps everything.
4. Review the result tabs: matched / changed, only on left, only on right, duplicate keys, and the joined CSV preview.
5. Copy or download the joined CSV, or copy the change report for tickets and PRs.
6. For row-level value comparison only (no join), use the List Comparator; for JSON exports, use JSON Diff.

Tips & pitfalls

• Choose a stable key. Comparing by row index is unreliable — sorts and inserts will report wrong changes.
• Resolve duplicate keys before trusting the diff. Duplicates inflate matches and hide changes.
• Trailing whitespace and casing differ silently — enable trim and case-insensitive matching for emails and codes.
• If a CSV uses semicolons or tabs, set the delimiter manually; auto-detection fails on tiny files.
• For very wide CSVs, hide unchanged columns so the diff stays readable.

FAQ

• How do I compare two CSV files by key? Load both files, pick the shared key column (e.g., id or email), and the tool produces matched/changed rows, only-on-left, only-on-right, and a joined CSV.
• What is the difference between join and compare here? Join produces a combined CSV; compare produces a diff report. The tool does both at once — pick a join type to control which rows appear in the export.
• Can I use a composite key (multiple columns)? Yes — select multiple key columns to handle natural keys like (tenant_id, user_id).
• Is my CSV uploaded? No. Parsing, joining, and diffing all happen in your browser. Nothing is sent to a server or logged.
• What if my files have different column names? Pick the matching column on each side as the key; non-key columns are compared by header name and shown as missing when only one side has them.
• How big can the CSVs be? The tool handles tens of thousands of rows comfortably; multi-million-row files may be slow — split by partition or load into a database for those.

Related tools

• Compare two lists for a quick set difference without a key column.
• View and clean CSV data before reconciling two exports.
• Build SQL IN clauses from the keys that differ between files.
• Diff JSON exports when your data is JSON rather than CSV.

Use-case guides

• Compare two CSV files by key
• Find missing rows between two CSV files

Runs locally in your browser. No uploads. No analytics on pasted CSV data.