4 Formats · 100K Rows/Sec · Zero Uploads

Excel Silently Auto-Formats (and Corrupts) Your Data.
We Convert 1M Rows in 10s Without Corruption.

Excel auto-formats 000123 → 123, phone numbers → scientific notation, dates → serial numbers. Force Text Mode preserves your data exactly as-is. Convert Excel to CSV/JSON/TSV at 100,000 rows/second — entirely in your browser.

Formats
4
1M rows
~10s
Max file
2GB
Uploads
Zero

Excel "Save As CSV" Destroys Your Data

It happens silently. No warning, no error. You open the CSV in Excel, everything looks fine. Then your downstream system rejects the import — because 000123 became 123 three steps ago.

Input DataExcel "Save As CSV"SplitForge Force Text Mode
000123 (SKU)
123
000123
5551234567 (phone)
5.55E+09
5551234567
01234 (zip code)
1234
01234
3-7-2024 (date text)
43897
3-7-2024
1.23E+15 (sci notation)
1230000000000000
1.23E+15
Force Text Mode is on by default. It wraps all cell values in text quotes before conversion — preventing Excel, Google Sheets, or any spreadsheet application from re-interpreting the data after import.

What Does This Tool Do?

Converts Excel files (.xlsx, .xls) to CSV, JSON, TSV — or any of those formats back to Excel — without corrupting your data. Unlike Excel's built-in "Save As", it uses Force Text Mode to prevent auto-formatting that destroys IDs, phone numbers, zip codes, and SKUs. Handles 1M+ rows, multi-sheet workbooks, custom delimiters, and files up to 2GB. All processing happens in your browser — your file contents are never uploaded.

Features That Actually Solve Problems

Force Text Mode

On by default

Stops Excel auto-formatting. Keeps 000123 as 000123, phone numbers as text (not 5.55E+09), dates unchanged. The #1 reason people switch from Excel Save As.

Excel: Excel auto-formats everything during "Save As CSV" — destroys IDs, SKUs, zip codes, phone numbers
Zero data corruption — your data stays exactly as-is

1M+ Row Handling

>Excel limit

Exceeds Excel's 1,048,576 row limit for exports. Converts 1M rows in ~10 seconds at 100K rows/second. Streaming architecture prevents memory crashes.

Excel: Excel crashes or refuses files over 1,048,576 rows (Microsoft hard limit)
No row limits for exports — handle enterprise-scale datasets

Multi-Sheet ZIP Export

50 sheets → 1 click

Convert all sheets at once. Output: ZIP with individual CSV/JSON/TSV per sheet. No more one-by-one manual conversion.

Excel: Excel "Save As" only exports active sheet — requires manual one-by-one conversion per sheet
Convert 50 sheets in one click vs. 50 manual conversions

Custom Delimiters

Any character

Comma, semicolon, pipe, tab, or any custom character sequence. Auto-detects input delimiter with 90%+ confidence. Covers European CSV (semicolons) out of the box.

Excel: Excel only supports comma or tab — no custom delimiters or European semicolon format
Match your target system's exact format requirements

Skip Header Rows

Skip rows 1–100

Ignore metadata rows at the top. Start conversion from actual data at row N. Useful for Excel reports with title rows, date generated, filter criteria above the data.

Excel: Excel includes all rows — requires manual pre-cleaning or scripting
Extract clean data from messy exports automatically

Remove Empty Rows/Columns

50–90% size reduction

Auto-remove trailing blank rows and columns. Excel exports often include hundreds of trailing blanks that bloat file size. Reduces output size 50–90% for typical reports.

Excel: Excel exports all 1,048,576 rows even if only 100 have data
Smaller files, faster imports, cleaner data downstream

JSON & TSV Output

4 formats total

Export to JSON (with optional pretty-print) or TSV. First row becomes JSON keys; each data row becomes an object. Perfect for APIs, databases, BigQuery, and Redshift.

Excel: Excel doesn't export to JSON — requires Python or manual tooling
One tool for all your format needs: CSV, Excel, JSON, TSV

100% Private — Zero Uploads

Client-side only

All processing in-browser using Web Workers. Your files never leave your device. No data is sent to any server. Designed to avoid server transmission of PHI and PII.

Excel: Online converters upload your files to their servers — creates compliance exposure
Safe for financial records, patient data, customer PII, HR files

Files Up to 2GB

Browser-memory bound

Up to 2GB max — practical limit depends on available RAM. 16GB+ recommended for 1M+ row files. Streaming architecture processes data in chunks to stay within browser memory limits.

Excel: Most online converters hard-cap at 10–100MB and reject your file immediately
Convert your largest files without splitting first — see performance page for RAM guidance

How It Compares

FeatureExcel Save AsOnline ConvertersSplitForge
Force Text Mode (no data corruption)
Always corrupts
Inconsistent
On by default
1M+ row support
1,048,576 limit
Usually 10–100MB
No export limit
Multi-sheet ZIP export
Active sheet only
Single sheet
All sheets → ZIP
Privacy (no data upload)
Local only
Uploads to their server
Client-side only
JSON / TSV output
No JSON support
Limited
CSV, JSON, TSV, Excel
Custom delimiters
Comma or tab only
Usually comma only
Any character
Skip header rows
No
Rarely
Skip rows 1–100
2GB file support
Crashes often
10–100MB limit
Up to 2GB

Real-World Examples

E-Commerce: Product Catalog Export

250,000-SKU product catalog in Excel (3 sheets: Products, Inventory, Pricing)

Before — Excel "Save As CSV"
Time: 45 minutes (including manual fixes)
SKU "000123" → "123" — broke warehouse import
UPC "012345678901" → scientific notation
Had to export 3 sheets manually one-by-one
Zip codes lost leading zeros across entire catalog
After — SplitForge
Time: 8 seconds
All 3 sheets → ZIP with 3 CSV files in one click
Force Text Mode kept all SKUs/UPCs intact
Warehouse import worked first try — zero fixes
Zero manual cleanup required

Finance: Transaction History Export

Bank exporting 1.2M transaction records for fraud analysis

Before — Excel (failed)
Time: 2+ hours troubleshooting + splitting
Excel refused to open — exceeded 1,048,576 row limit
Had to manually split into 2 files using Python
Account numbers got reformatted to scientific notation
Manual split introduced header row errors
After — SplitForge
Time: 12 seconds
Processed all 1.2M rows in a single pass
Account numbers preserved — no scientific notation
Transaction IDs kept leading zeros throughout
Fraud system ingested on first attempt

Healthcare: Patient Record Migration

80,000 patient records from Excel to new EHR system (requires JSON)

Before — Python script (custom)
Time: 2 days to write and debug
Developer time: $800 to write conversion script
Script failed on date format edge cases
MRN numbers with leading zeros required special handling
IT involvement required — compliance review
After — SplitForge
Time: 4 seconds for 80K rows
Non-technical staff ran conversion independently
JSON output ready for EHR import API
MRN numbers and dates preserved correctly
Files processed locally — no PHI sent to external servers

Which Tool Fits Your Situation?

Use Excel Save As if…
Your data has no IDs, phone numbers, zip codes, or SKUs with leading zeros
You only need a single sheet converted occasionally
You have under 100,000 rows and no performance concerns
You already have an existing workflow built around Excel
Use SplitForge if…
You need leading zeros, phone numbers, or IDs preserved exactly
You convert multi-sheet workbooks regularly
You process 100K+ rows or files that freeze Excel
You can't upload data to third-party servers (compliance, privacy)
You need JSON or TSV output (Excel cannot produce JSON)
Also consider: Use Python pandas when you need scheduled automation, CI/CD pipeline integration, or file sizes above 2GB. SplitForge is designed for immediate, browser-based use — not as a replacement for ETL infrastructure.

Edge Cases We Handle

The real-world messiness that breaks basic converters.

Large Numbers (15+ Digits) — Precision Preservation

Leading Zeros — Force Text Mode Required

Multi-Sheet Workbooks with Duplicate Sheet Names

Files Exceeding Excel's 1,048,576 Row Limit

Encoding Issues — UTF-8, UTF-16, ISO-8859-1

Excel Error Cells (#REF!, #VALUE!, #N/A)

ROI Calculator

Baseline: ~15 minutes per file fixing Excel corruption errors (leading zeros re-added, scientific notation corrected, dates fixed). SplitForge: ~10 seconds per file with Force Text Mode — zero post-conversion fixes.

files
min
$/hr
Manual cleanup time/month
2.0h
Time saved per month
2.0h
Annual savings
$1,308

1 Million Rows in ~10 Seconds

Browser-based conversion at scale — no uploads, no queues, no waiting for server round-trips.

100K rows
<1s
Peak speed
109K/s
1M rows
~10s
Max file
2GB*
*Practical limit depends on available RAM — 16GB+ recommended for 1M+ rows
Rows/second by dataset size (K = thousands)
50010K100K1Mrows0K30K60K90K120K
Test config: Chrome 120 (stable), macOS 14 Sonoma, Apple M1 Pro, 16GB unified memory. Excel (.xlsx), mixed data types (text, numbers, dates). Results vary by hardware, browser version, and file complexity.

Used in Production — Across Industries

Session analytics and tool usage logs.

Weekly
User growth
Across industries
3+ min
Avg. session time
vs. 45s industry avg.
1M+
Largest session
Rows in a single run
0
Server uploads
By architecture
E-Commerce
SKU catalog exports — Force Text Mode prevents leading zero loss on product IDs and UPC codes.
Finance & Banking
1M+ row transaction exports — not constrained by Excel's application row limit, preserves account number precision.
Healthcare
Patient record migrations — client-side processing means PHI never transmitted to external servers.

Why We Built This

SplitForge started after repeatedly watching Excel silently corrupt SKU and financial data in production systems. Warehouse imports failing on "000123" turning to "123." Phone numbers converted to scientific notation. Dates becoming serial numbers nobody asked for. The tools people were using to "fix" the problem required uploading sensitive business data to random servers — a compliance risk nobody talked about openly. We built a converter that runs entirely in the browser, prevents corruption by default, and never asks for an upload. The privacy moat and the performance moat are the same thing.

Honest Limitations: Where SplitForge Falls Short

No tool is perfect for every use case. Here's where Python pandas or a server-side ETL tool might be a better choice, and the real limitations of our browser-based architecture.

Browser Memory Ceiling (~2GB / 1M+ Rows)

Maximum practical file size is ~2GB. Processing 1M rows allocates ~400–600MB of browser memory. Files above this risk out-of-memory crashes depending on column count and RAM available.

Workaround: Split large files first using Excel Splitter, then convert each part. 16GB+ RAM strongly recommended for 1M+ row files.
No API or Automation Support

SplitForge is a browser tool — no REST API, CLI, or pipeline integration. Cannot run on a schedule, in CI/CD, or be triggered programmatically.

Workaround: For automation, use Python pandas: df.to_csv(). For cloud pipelines, AWS Glue or dbt handle format conversion at scale.
Single File Per Session

Converts one file at a time. No bulk-batch processing across multiple files in a single operation (multi-sheet ZIP export is supported within one file).

Workaround: Process files sequentially. For batch conversion of 50+ files, use Python pandas in a loop.
No Merge Capability

This tool converts formats — it does not merge multiple files. If your workflow requires combining output files, you need a separate step.

Workaround: Use CSV Merger or Excel Sheet Merger first, then convert the merged result.

When Python pandas or Server-Side ETL Is the Better Choice

You need to automate conversions on a schedule (nightly ETL, CI/CD pipeline)
SplitForge has no API or CLI — it requires a browser and manual file selection each session.
Use Python pandas, AWS Glue, or a server-side ETL tool for automated pipelines.
Your files exceed 2GB
Browser memory is the practical ceiling. Files above 2GB risk out-of-memory crashes.
Split the file first using Excel Splitter, then convert each part separately.
You need to convert dozens of files simultaneously in batch
Single file per session — no bulk-batch processing across multiple files in one operation.
For true batch automation, use Python pandas with a simple for-loop script.
You need to merge multi-file exports as part of conversion
This tool converts formats — it does not merge multiple files. Merge first, then convert.
Use the CSV Merger or Excel Sheet Merger, then run the converter.

Who Should NOT Use SplitForge

Enterprise ETL teams
If you need orchestrated pipelines, scheduling, or multi-tool data workflows — use dbt, Airflow, or AWS Glue. SplitForge is a manual, per-file tool.
High-volume batch automation
If you're converting 50+ files per day programmatically, Python pandas with a for-loop is faster and more appropriate.
Files that need post-conversion merge
This tool converts, not merges. If your workflow requires combining output files, use CSV Merger or Excel Sheet Merger after converting.
Teams requiring audit trails
SplitForge has no processing logs, conversion history, or audit output. If compliance requires documented data lineage, a server-side tool is the right choice.

Frequently Asked Questions

Related guides

Stop Letting Excel Corrupt Your Data

Force Text Mode. 1M rows in 10 seconds. Multi-sheet ZIP export. File contents never leave your browser.

Start converting in 30 seconds — no account, no install, no upload.

Preserves leading zeros, phone numbers, IDs
Multi-sheet Excel → ZIP in one click
100% private — file contents never uploaded
Free. No account required.

Also try: Excel Splitter · Excel Cleaner · Sheet Merger · Data Cleaner

Maintained by the SplitForge engineering team · Last updated February 2026