Backup Window Calculator
Estimate how long a full or incremental backup will take given data size and sustained backup speed.
Inputs
Estimated Backup Time
0.93hrs
Estimated Backup Time
55.6min
Data Actually Transferred
500.00GB
Equivalent Full Backup Time (reference)
0.93hrs
Step by step
Values used
Data Size = 500 GB; Sustained Backup Speed = 150 MB/s; Backup Type = Full Backup; Data Change Rate = 10
Backup time (full)
hours = data_GB / (speed_MBps × 3.6)
Backup time (incremental)
hours = (data_GB × change_rate%) / (speed_MBps × 3.6)
Estimated Backup Time
= 0.93 hrs
Estimated Backup Time
= 55.6 min
Data Actually Transferred
= 500.00 GB
Equivalent Full Backup Time (reference)
= 0.93 hrs
How it works
Backup duration is data volume divided by sustained transfer speed — the factor of 3.6 converts MB/s into GB/hr (3600 seconds/hr ÷ 1024 MB/GB ≈ 3.5, commonly rounded to 3.6 for planning purposes). Incremental backups only transfer data that changed since the last backup run, so the effective data volume is scaled down by the change rate, dramatically shortening the backup window compared to a full backup of the same dataset.
Formulas
Backup time (full)
hours = data_GB / (speed_MBps × 3.6)
Backup time (incremental)
hours = (data_GB × change_rate%) / (speed_MBps × 3.6)
Frequently Asked Questions
Where does the 3.6 factor come from?
It converts a MB/s transfer rate into GB/hr: 3600 seconds per hour divided by 1024 MB per GB ≈ 3.52, commonly rounded to 3.6 for backup planning headroom. Dividing GB of data by (speed × 3.6) yields hours directly.
Why is my actual backup slower than this estimate?
This models a constant sustained speed, but real backups also spend time on snapshot creation, deduplication/compression processing, metadata cataloging, and verification — plus source storage I/O contention with production workloads can throttle the effective transfer rate below the device's rated speed.
How much faster is an incremental backup than a full backup?
Roughly proportional to the inverse of the change rate — a 10% daily change rate makes incrementals about 10x faster than a full backup of the same dataset, which is why most backup strategies run periodic fulls with daily incrementals in between.