Benchmark Performance
Detailed Performance Metrics
| File Size | Processing Time | Notes |
|---|---|---|
| 1M | ~3.5-4.5 sec | 2 columns masked (email + phone) |
| 5M | ~18-22 sec | 2 columns masked (email + phone) |
| 10M | ~35-45 sec | 5 columns masked (all PII types) |
Projected at ~250,000 rows/sec • actual throughput varies by hardware and browser • file contents processed 100% in-browser.
Calculate Your Time Savings
Typical: 1M-5M rows
Weekly = 52, Monthly = 12
Analyst avg: $45-75/hr
- Manual masking eliminated: 5.99 hours saved
- Compliance documentation automated: PDF reports included
- Automated PII detection: Reduces missed sensitive data
- Example baseline: $50-120/month AWS costs avoided (sessions + S3 + egress)
Testing Methodology
How we measure performance and ensure accuracy
Honest Limitations: Where SplitForge Data Masking Falls Short
No tool is perfect for every use case. Here's where AWS Glue DataBrew / Informatica might be a better choice, and the real limitations of our browser-based architecture.
Browser-Based Processing
Performance depends on your device's RAM and CPU. Modern laptops (2022+) handle 10M+ rows easily, but older devices may struggle with very large files.
No Offline Mode (Initial Load)
Requires internet connection to load the tool initially. Processing happens offline in your browser after loading.
Browser Tab Memory Limits
Most browsers limit individual tabs to 2-4GB RAM. This is the practical ceiling for file size.
Largest Tested File (~1.4GB)
The largest file tested is ~1.4GB (~10M-20M rows). CSV/TSV output streams at constant memory (~13MB heap at 10M rows), so this is a tested ceiling, not a fixed memory cap. XLSX output is limited to 1,048,576 rows (one Excel sheet). Much larger datasets may still be bounded by the time to read the input file.
No API or Automation Support
SplitForge is a browser-based tool without API access. Can't integrate with CI/CD pipelines or automated workflows.
Limited Advanced Transformations
SplitForge focuses on masking only. Can't do joins, aggregations, filtering, or complex ETL transformations like AWS Glue recipes or Informatica mappings.
Single-User Processing (No Collaboration)
SplitForge is single-user. Can't share masking configurations or audit trails across teams like AWS Glue projects or Informatica workspaces.
When to Use AWS Glue DataBrew / Informatica Instead
You need 100M+ row datasets processed daily
AWS Glue DataBrew and Informatica scale horizontally with parallel cluster processing. SplitForge is browser-limited to ~20M rows max.
You need API-driven automation and CI/CD integration
SplitForge has no API. Enterprise tools have full REST APIs for automated workflows.
You need complex data transformations + masking in one tool
AWS Glue DataBrew has 250+ transformation recipes, Informatica has visual ETL mappings. SplitForge only masks.
You're already AWS-native with Glue ETL pipelines
If you're using AWS Glue ETL, Athena, and Redshift, DataBrew integrates seamlessly. SplitForge requires manual file export/import.
Questions about limitations? Check our FAQ section below or contact us via the feedback button.
Related Resources
Frequently Asked Questions
How accurate are these benchmarks?
Why use ranges instead of exact numbers?
How does RAM affect performance?
How does this compare to AWS Glue DataBrew?
How does SplitForge compare to manual Excel redaction?
What file sizes have been tested?
Does masking speed vary by PII type?
How often should benchmarks be updated?
Can I reproduce these benchmarks?
What's the slowest operation in the masking process?
Why not just use Python or AWS for everything?
How does client-side processing compare to cloud-based tools?
Last Updated: February 2026 · figures are modeled projections, not per-run benchmarks