Row-based splitting is the most direct way to divide a large dataset, treating every row equally and dividing them into groups of your chosen size, without needing to consider column values, dates, or any other data-specific logic.
Turbo Large Data Splitter's Number of Rows method does exactly this: every output part gets the same number of rows, up to 1,000,000 rows per file, working across CSV, TSV, TXT, XLSX, JSON, and XML input, regardless of the dataset's original format.
This is the most common way to split a file into multiple files for import into another system, whether that's a database with a batch size limit, a reporting tool with a comfortable row count, or simply a size that feels manageable for manual review.
Splitting an Excel file by row also removes the roughly 1,048,576-row-per-sheet ceiling Excel itself imposes on a single worksheet, since each part becomes its own workbook once split.
Preview reports your total row count and calculates how many output files your chosen setting will produce, so you know exactly what to expect before committing to the actual split.
Everything runs offline, entirely on your own Windows PC, so splitting a large dataset by row count never requires uploading any of your data to an external service. Delimiter and encoding both default to Auto for relevant formats and are detected directly from the file itself, so you only need to touch them in the rare case detection gets something wrong, an unusual delimiter or a legacy encoding, for example. This makes the tool equally useful for data analysts working with irregular exports, developers automating a recurring pipeline step, e-commerce teams distributing catalog data by category, and anyone else who regularly runs into the practical limits of opening a large data file directly in a spreadsheet program.













- Install Turbo Large Data Splitter on your Windows PC.
- Browse to or drag and drop your dataset.
- Choose your output folder and format.
- Select the Number of Rows split method.
- Set your desired rows per file, up to 1,000,000.
- Run Preview to confirm the row count and estimated files.
- Click Start Split and monitor progress.
- Open the output folder once the split completes.
- Adjust the parallel worker slider if compressing many output parts.
- Check the status bar for the final row count and file count summary.
- Splits by a fixed row count, up to 1,000,000 rows per file
- Works across CSV, TSV, TXT, XLSX, JSON, and XML
- Removes Excel's roughly 1,048,576-row-per-sheet ceiling
- Preview confirms the exact resulting file count
- Consistent, predictable file sizes throughout
- Streaming engine handles files of any size
- Runs fully offline with no uploads required
- One-time purchase for Windows, with Gumroad license activation
- Compression options: uncompressed, per-part ZIP/gzip, or a single bundled archive
- Works with files on local drives, external drives, and network shares
What's the maximum rows per file I can set?
Rows per file can be set up to a ceiling of 1,000,000 rows.
Does this work for Excel files too, or only CSV?
It works across all supported formats, including XLSX, so an Excel file can be split by row count the same way as a CSV file.
Does splitting by rows help with Excel's own row limit?
Yes, splitting an Excel file into multiple parts by row count removes the roughly 1,048,576-row-per-sheet ceiling, since each part becomes its own workbook.
How do I know how many files a given row count will produce?
Preview reports the total row count and calculates the resulting output file count based on your chosen rows-per-file setting.
Does this work on both Windows 10 and Windows 11?
Yes, Turbo Large Data Splitter is built and tested for both Windows 10 and Windows 11.
Is my data safe when using this tool?
Yes, all processing happens locally on your PC; no files are ever uploaded, so proprietary or sensitive data stays fully under your control.
Can I compress the split output files?
Yes, you can leave parts uncompressed, zip or gzip each part individually, or bundle everything into a single ZIP or gzip archive, sped up by a parallel worker slider.
Can I use this on files stored on an external or network drive?
Yes, data files on local drives, external drives, or mapped network shares all work the same as any local file.
Can I cancel a split job partway through if I need to?
Yes, cancelling saves a checkpoint file in the output folder, so you can resume the job later exactly where it left off instead of starting over.
Is there a trial version available before buying?
Check the product page on turbo-soft.com for current trial availability and details.
Ready to split your large dataset by number of rows, fully offline?