Supported File Format
Turbo CSV Splitter is built to do one job well: split large CSV files into smaller, well-formed CSV files. Delimiters and encodings are detected automatically, so you can drop in a file and start splitting right away.
9 Ways to Split a CSV File
| Number of Rows | → | Every output file gets the same row count, up to 1,000,000 rows per file. |
| File Size | → | Rolls over to a new part once it reaches your target size in MB. |
| Column Value | → | Writes one output file per distinct value found in a chosen column. |
| Date Column | → | Groups rows by day, month, or year based on a date column, auto-parsing common date formats. |
| Alphabet | → | Buckets rows into A-F / G-L / M-R / S-Z / 0-9 / Other, based on the first letter of a column's value. |
| Duplicate Values | → | Splits rows into a "duplicates" file and a "first seen" file. |
| Unique Values | → | Keeps only the first occurrence of each row, dropping every later duplicate. |
| Equal Parts (N Files) | → | Splits the file into exactly N roughly-equal files (a quick row count runs first). |
| Random Shards (N Files) | → | Randomly assigns every row to one of N output files - ideal for train/test/validation splits. A seed makes the assignment reproducible, even on resume. |
Key Features
▶ Split Tab
Pick your input CSV (Browse, or drag-and-drop onto the drop zone), choose an output folder, select a split method, and click Start Split. Delimiter and encoding default to Auto. Progress, live speed in rows/sec, and an ETA appear in the status bar as the job runs.
▶ Merge Tab
Combine two or more CSV files - including previously split parts - back into a single CSV, with the header written only once. Optionally tag each row with its source filename, remove duplicate rows across all files, and sort the combined result by a column.
▶ Profile Tab
Scans a CSV and reports, per column: non-null/blank counts, distinct value counts, min/max text length, and (for numeric-looking columns) the min, max, and mean. Flags ragged rows with a different field count than the header. Export the report to a text file.
No Excel Row Limit
Split files with tens of millions of rows into parts that open cleanly in Excel or any spreadsheet tool, without ever hitting the 1,048,576-row ceiling.
Streaming Engine for Huge Files
Rows are read and written one at a time rather than loaded into memory, so multi-GB and 100 GB+ CSV files are supported as long as there's free disk space for the output.
Auto-Detect Delimiter & Encoding
Samples the file to detect comma, semicolon, tab, or pipe delimiters, and encodings including UTF-8, UTF-8-SIG, UTF-16, CP1252, and Latin-1. Override manually if needed.
Cancel & Resume From Checkpoint
Cancel a running job at any time - a checkpoint file is saved in the output folder. Click Start Split again with the same file and settings to resume exactly where you left off instead of starting over.
Run Preview Before You Split
Run Preview to see the total row count, detected columns, ragged-row warnings, sample rows, and an estimate of how many output files you'll get - before committing to the full job.
Column Data Quality Profiling
Spot data-quality issues before you split or merge: null/blank counts, distinct-value counts, text length ranges, and numeric min/max/mean per column, plus a ragged-row count.
1-128 Parallel Workers
A worker slider from 1 to 128 speeds up compressing many output parts at once, scaling to match your CPU.
Drag & Drop Support
Drop a CSV file straight onto the app window instead of browsing for it, for a faster start to every split job.
Minimize to System Tray
Send the app to the system tray while a large split or merge job runs in the background, and reopen it from the tray icon when it's done.
Column Tools & Data Transformation
- Keep Only These Columns / Drop These Columns - comma-separated column names; if "Keep only" is filled in, "Drop" is ignored.
- Rename Columns - pairs like
old:new, old2:new2rename headers in the output without changing which data goes where. - Add Row Number Column - prepends a running row-number column, starting at 1, to every output file.
- Find & Replace - add one or more rules, optionally limited to a single column and with optional regex, applied to every row before it's written.
- Output Delimiter - leave blank to match the input delimiter, or set a different one to convert on the way out (e.g. comma-in, semicolon-out).
- Output Quoting - minimal, quote all fields, quote non-numeric fields, or no quoting.
- Line Ending - choose LF (Unix/Mac) or CRLF (Windows).
- Compression - leave parts uncompressed, zip or gzip each part individually, or bundle every part into one ZIP or .tar.gz archive.
Filtering, Sorting & Deduplication
Simple Filter
Pick a column, an operator (equals, contains, starts with, greater than, is blank, and more), and a value - no coding needed.
Advanced Filter
Write a Python expression using row as the row dictionary, e.g. row["Country"] == "USA", applied in addition to the simple filter.
Sort by Column
Optional chunked external merge-sort so even huge files sort correctly without exhausting RAM, ascending or descending.
Remove Duplicate Rows
Drops exact duplicate rows, compared across all columns, before the file is split or merged.
Safety and Reliability
- Checkpoint & Resume - a small checkpoint file is written to the output folder during every split job, so a cancelled or crashed run can resume from where it stopped.
- Fingerprinted Checkpoints - a checkpoint only resumes when the input file and settings match; if anything changed, the job starts fresh instead of applying stale progress.
- Ragged Row Handling - rows with a different number of fields than the header are padded or truncated safely and flagged in Preview and Profile rather than crashing the job.
- Fail-Open Filtering - if an advanced filter expression errors on a row, that row is kept rather than silently dropped, so a typo in a filter can't quietly delete data.
- Atomic Checkpoint Writes - checkpoint files are written to a temporary file and swapped in, avoiding a corrupted resume state if the app is closed mid-write.
- Stable Under Heavy Loads - streaming reads and writes keep memory use flat, even across files with tens of millions of rows.
- Ideal for Sensitive Environments - analytics teams, finance and ops teams, data engineers, and air-gapped networks working with exported CSV data.
Performance and Speed
Streaming, Not Loading
Rows are read and written one at a time, so memory use stays flat regardless of file size - no pandas-style full-file load into RAM.
Real-Time Rows/Sec & ETA
The status bar shows live throughput in rows per second and a dynamically updated estimated time remaining while a split or merge job runs.
Parallel Compression
When compression is enabled, output parts are compressed across up to 128 workers in parallel instead of one at a time.
External Merge-Sort
Sorting by column uses a chunked, disk-backed merge-sort so files far larger than available RAM can still be sorted correctly.
Fast Delimiter/Encoding Detection
Detection samples only the first portion of the file rather than scanning the whole thing, so even huge files open quickly.
Massive File Capability
Suitable for exported database dumps, analytics logs, e-commerce catalogs, survey data, and multi-gigabyte CSV exports from other systems.
Security and Privacy
Turbo CSV Splitter is a fully local desktop application. All splitting, merging, and profiling happens on your own computer. No files are uploaded, scanned remotely, or shared with third parties. It is a trusted offline CSV splitter for personal, business, and enterprise data workflows.
- Does not log, analyze, track, or store the contents of your CSV files
- No integration with third-party analytics, advertising trackers, or background telemetry
- Internet is used only for license validation - the request contains no file names or file content
- Ideal for analysts, data engineers, businesses, and teams handling exported or sensitive data
- Complete confidentiality for personal, professional, and commercial workflows
Minimum System Requirements
| Operating System | Windows 8 (64-bit) |
| Processor | 1-2 CPU cores |
| Memory | 2 GB RAM |
| Storage | Free disk space at least equal to the size of your split or merge output |
Recommended System Requirements
| Operating System | Windows 10 or later (64-bit) |
| Processor | 4 or more CPU cores |
| Memory | 8 GB RAM or more |
| Storage Type | SSD recommended for best throughput on large files |
| Free Disk Space | Enough headroom for input, output, and temporary sort files |
App Info
| App Name | Turbo CSV Splitter |
| Version | 1.1 |
| Platform | Windows |
| Category | Data Tools / CSV Utilities |
| License Management | Gumroad |
A Fast, Reliable CSV Splitter for Windows
Turbo CSV Splitter is a dedicated CSV splitter, CSV merger, and column profiler built for large, unwieldy CSV exports. It processes everything locally on your computer - no uploads, no cloud services, no file-size limits, no waiting queues - making it ideal for data analysts, developers, e-commerce teams, and anyone who regularly hits Excel's 1,048,576-row wall. As a complete tool for splitting large CSV files on Windows 11 and Windows 10, it supports splitting by row count, file size, column value, date, alphabet, duplicate status, equal parts, or random shards, so you can split a CSV by rows for spreadsheet-friendly chunks, split a CSV by column for one-file-per-category exports, or generate random shards for machine-learning train/test/validation splits. Everything streams row by row rather than loading the whole file into memory, so multi-GB and 100 GB+ CSV files are supported as long as there's enough free disk space for the output. It's also a full-featured CSV merge tool and CSV column profiler in one lightweight desktop install, with no separate scripts, notebooks, or web apps required.
Looking for other batch data or file tools from TurboSoft? Million by Million Rows Copier moves huge spreadsheet ranges to the clipboard in chunks, and the Bulk Renaming Tool cleans up filenames across thousands of files in one pass.
Frequently Asked Questions
Common Questions About Turbo CSV Splitter
How do I split a CSV file that's too big for Excel?
Open Turbo CSV Splitter, browse to your CSV file, choose Number of Rows as the split method, set rows per file (up to 1,000,000), and click Start Split. Excel's 1,048,576-row limit is never hit because each output file stays under your chosen size.
Can it split a CSV file by column value?
Yes. Choose the Column Value split method and pick a column - Turbo CSV Splitter writes one output CSV per distinct value in that column, so you could split a sales file into one file per region or per customer automatically.
Does it work on huge multi-gigabyte CSV files?
Yes. Turbo CSV Splitter streams the file row by row instead of loading it into memory, so multi-GB and 100 GB+ CSV files are supported as long as there's enough free disk space for the output.
Can I merge split CSV files back into one?
Yes. The Merge tab combines two or more CSV files back into a single file, writing the header only once. You can optionally tag each row with its source filename, remove duplicate rows, and sort the combined result by a column.
What happens if a split job is interrupted?
Turbo CSV Splitter saves a checkpoint file in the output folder. If a job is cancelled or the app crashes partway through, clicking Start Split again with the same file and settings resumes exactly where it left off instead of starting over.
Can it split CSV files by date?
Yes. The Date Column split method groups rows by day, month, or year based on a date column you select, automatically parsing common date formats and writing one file per time bucket.
Does it detect the CSV delimiter and encoding automatically?
Yes. Delimiter and text encoding are set to Auto by default, and Turbo CSV Splitter samples the file to detect comma, semicolon, tab, or pipe delimiters and common encodings like UTF-8, UTF-8 with BOM, UTF-16, CP1252, and Latin-1.
Can I remove duplicate rows while splitting?
Yes. Turn on Remove Duplicate Rows to drop exact duplicates (compared across all columns) before the file is split, or use the dedicated Duplicate Values and Unique Values split methods to separate duplicates from first-seen rows.
Is there a tool to check data quality before splitting a CSV?
Yes. The Profile tab scans a CSV and reports, per column, non-null and blank counts, distinct value counts, min/max text length, and numeric min/max/mean - plus it flags ragged rows that have a different number of fields than the header.