Data Merger

About Data Merger

Data Merger is a free online tool that combines multiple CSV or JSON files with the same schema into a single unified file. Upload multiple data files, choose your merge settings, and download the combined result—all processed locally in your browser for complete privacy.

Why merge multiple data files?

Merging data files is essential for many scenarios:

- Combining monthly/yearly reports into a single dataset
- Aggregating data from multiple sources or departments
- Consolidating backup files or exports
- Preparing data for analysis or visualization
- Cleaning up fragmented data collections

Instead of manually copying and pasting data between files, this tool automates the process with powerful merge options.

What's the difference between Union and Intersect modes?

The merge mode determines how columns are handled:

Union Mode (Default):
- Keeps ALL columns from all files
- Missing values filled with null/empty
- Best when files have mostly the same structure
- Example: File1 (A,B,C) + File2 (B,C,D) = Output (A,B,C,D)

Intersect Mode:
- Keeps ONLY columns present in ALL files
- Ensures consistent schema across all rows
- Best for strict data consistency
- Example: File1 (A,B,C) + File2 (B,C,D) = Output (B,C)

How does duplicate removal work?

When 'Remove Duplicate Rows' is enabled, the tool identifies and removes exact duplicate rows:

- Compares entire row content (all columns)
- Keeps the first occurrence, removes subsequent duplicates
- Uses efficient deduplication algorithm (Arquero library)
- Helpful when merging overlapping datasets

This is useful when combining files that may contain the same records, like monthly exports with overlapping data.

Can I merge CSV and JSON files together?

No, you must select files of the same format:

- CSV mode: Merge only CSV files
- JSON mode: Merge only JSON files

However, you can choose the output format independently:
- Merge CSV files → output as JSON
- Merge JSON files → output as CSV

This gives you flexibility to convert formats while merging data.

What if files have different column orders?

The tool handles different column orders automatically:

- For CSV with headers: Matches columns by header name, not position
- For JSON: Matches properties by key name
- Output maintains a consistent column order
- Missing columns filled with empty/null values (in Union mode)

This means you can merge files even if their columns are arranged differently.

Does my data leave my device?

No. All file merging happens entirely in your browser using JavaScript and the Arquero data processing library. Your files never leave your machine, ensuring complete privacy for sensitive data like customer records, financial data, or confidential reports.

The tool can handle large files efficiently in-memory without needing to upload data to any server.

Will my IDs or ZIP codes lose their leading zeros?

For CSV files, the parser uses dynamic typing, which converts numeric-looking text into numbers. This means values like '007' or '01730' lose their leading zeros (becoming 7 and 1730).

If your dataset contains ID numbers, ZIP/postal codes, phone numbers or account references where the leading zeros matter, prefix the value with a quote/apostrophe or use JSON input (where strings are preserved), and verify the output before saving. JSON merging keeps the original value types exactly as written.

How are mismatched columns filled, and is there a row or file size limit?

In Union mode, every column found across all files is kept; rows from files that lack a column get a null value in that column. In Intersect mode, only columns present in every file are kept. The Merge Summary in the Information panel reports the final column list and the number of null-filled cells, so you can immediately spot schema mismatches.

There is no hard row or file limit. Because everything runs in your browser's memory, practical limits depend on your device's available RAM. Files up to tens of MB and hundreds of thousands of rows merge comfortably on a typical machine; very large datasets may slow down or hit browser memory limits.