Split large CSV, TSV, JSON, XML, TXT, Excel, SQL and LOG files in minutes with 100% local processing. No data upload, no security risks - perfect for enterprise data analysis and processing.
DataFileSplitter offers flexible splitting options to handle all your large data file processing requirements
All file splitting happens on your local device - no data is uploaded to our servers. Ensures complete data security and privacy for enterprise use.
Split files by row count, column value for JSON, XML, SQL, Excel, CSV, TSV, TXT, LOG formats.
Full command line interface for batch processing and automation. Integrate with your existing data pipelines and scheduled tasks.
Set up automatic splitting tasks to run at specific times. Perfect for regular processing of large data exports and reports.
Full support for UTF-8 and other encodings, ensuring proper handling of international characters and special symbols.
Save your splitting configurations and reload them later. Avoid reconfiguring complex splitting rules for recurring tasks.
DataFileSplitter works with all common data file formats used in enterprise environments
Trusted by data professionals and enterprises worldwide for fast, safe and reliable file splitting
"DataFileSplitter saved our team over 10 hours per week splitting large CSV files for our analytics pipeline. The local processing feature was a game-changer for our data security compliance."
"As a Mac user, I struggled to find a reliable file splitter that supports both JSON and Excel. DataFileSplitter works flawlessly across all our devices and the command line support is excellent for automation."
"We process millions of rows of log files daily, and DataFileSplitter handles it in minutes. The scheduled splitting feature allows us to automate the entire process without manual intervention."
Get answers to the most common questions about DataFileSplitter
Download the free 30-day trial today - no credit card required. Experience fast, safe and reliable file splitting for your enterprise needs.
Download Free Trial (v2.4)Available for Windows (32/64 bit), MacOS, Linux (deb/rpm)