![]() It supports reformatted and damaged drive restoration and comes with rapid scanning tools to reduce downtime and improve efficiency. Recovered files can be restored directly to a virtual hard drive (VHD), and it even supports recovery from damaged VHDs. It allows you to retrieve corrupted or otherwise inaccessible data and supports a range of external storage devices.Ĭonfidential or sensitive files can be destroyed with the secure overwrite tools.ĮaseUS is arguably even more powerful, with impressive Windows and Mac-specific features. Files can be restored while a scan is in progress, and you can even preview recovered files before saving them.įinally, Stellar supports all known file formats and allows you to add custom formats if necessary. Optical media recovery is possible, while RAID, non-bootable, encrypted, and virtual drive storage scanning is fast and simple. ![]() Overall, Stellar just comes out ahead here because it supports a comprehensive range of devices and all file types. Stellar Data Recovery allows you to recover any file from almost any device. ![]() To facilitate an accurate comparison between Stellar, EaseUS, and Recuva, we intentionally deleted a selection of files from the hard drive of our Windows test laptop (which has 8GB of RAM and a 1TB hard drive). We then completed standard and deep scans with all three programs to determine how well they work. They all successfully retrieved the test files, along with thousands of others that had been deleted in the past.ĮaseUS was the fastest of the three programs, with a standard scan completed in under one minute. A deep scan took just over two and a half hours, and neither used more than 30% CPU or 250MB of RAM. Stellar was slightly slower, but it did use significantly more computer resources. A quick scan took just under four minutes, and the deep scan took just over 12 hours. But both used over 75% CPU power and around 200MB of RAM, which means you could have trouble running Stellar alongside other programs.Īnd finally, Recuva’s rapid scan was also very quick, finishing in just over a minute. However, it took almost 24 hours to complete a deep scan, which is quite slow. In saying that, neither used more than 600MB of RAM or 10% CPU, which means it could be comfortably run in the background.
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