SheetXL Performance Benchmarks
Last Updated: August 4, 2025
Performance Matters
Performance is critical when working with large datasets or interactive spreadsheets.
SheetXL is optimized for performance across devices, letting you deliver fast, responsive experiences on any hardware.
This page provides transparent, reproducible benchmarks for common spreadsheet operations across a variety of hardware profiles and environments.
Our Testing Methodology
To ensure fairness and clarity, all tests were conducted using the following scenarios and environments. We encourage you to replicate these tests; all benchmarking scripts are available in our GitHub repository.
Test Scenarios
All tests were performed on a workbook containing 1,048,576 rows (2²⁰) and 5 columns (A-E) of pseudo-random numerical data.
- Initial Load: Time from component mount to the grid being rendered and interactive.
- Large Data Scroll: Measures UI smoothness (frame rate) while scrolling through the entire dataset. Reported as average Frames Per Second (FPS).
- Formula Autofill: Time to fill a new column (F) with a formula (
=SUM(A1:E1)) and autofill it down all 1,048,576 rows. This is our primary performance metric. - Complex Calculation: Time to recalculate the entire sheet after changing a single value in a precedent cell that affects thousands of dependent formulas.
- Data Sort: Time to sort the entire 1M+ row dataset by a single column.
- File Serialization (Node.js): Time to load a 50MB
.xlsxfile into a SheetXL instance in memory, and then save it back to a file.
Hardware Profiles
- High-End Desktop (M-Series): Apple Mac Studio (M2 Max, 32GB RAM)
- Mid-Range Laptop (Intel): Dell XPS 15 (Intel Core i7-11800H, 16GB RAM)
- Mobile Device (ARM): Samsung Galaxy S21 (Snapdragon 888, 8GB RAM) - from 2021
- Server Environment (Node.js): Standard AWS EC2
t3.largeInstance (2 vCPU, 8GB RAM)
Google Chrome Performance
Version 135. Average of 5 runs.
| Metric (1,048,576 rows) | High-End Desktop | Mid-Range Laptop | 4-Year-Old Phone |
|---|---|---|---|
| Initial Load (18MB) | 1.4 s | 1.6 s | 3 s |
| Large Data Scroll | ~60 FPS | ~55 FPS | ~48 FPS |
| Formula Autofill | 210 ms | 350 ms | 715 ms |
| Complex Calculation | 35 ms | 60 ms | 65 ms |
| Data Sort | 450 ms | 780 ms | 1.2 s |
Philosophy
SheetXL's performance is the result of a purpose-built, vectorized calculation engine. Unlike traditional data grids that struggle with complex calculations, or spreadsheet components that rely on inefficient cell-by-cell processing, our range-based API is designed for bulk operations.
This architecture allows SheetXL to deliver a fluid user experience even with massive datasets, all while running entirely client-side, reducing server costs and simplifying your infrastructure.
We are confident that these numbers represent a new standard for performance in web-based spreadsheets.
Ready to see for yourself?
Explore our demos or get started with our 2-minute quickstart guides.