Sneakernet

Sometimes in the world of computers, you get concepts that sound like they surely must be an April Fools’ joke but are actually a real thing. One example is ‘Sneakernet’.

The term Sneakernet refers to moving data by transferring it to a portable storage medium, such as a USB stick, a removable hard drive, or some DVDs, and then physically carrying that over to its destination. As you may have guessed, it’s referring to the user’s shoes as the means of transporting data, compared to Internet or Ethernet.

There’s also Internet Protocol over Avian Carrier, or IPoAC, to refer to sending data by carrier pigeon, which was actually proposed on the 1st of April in 1990. It is certainly possible to use carrier pigeons for sending SD cards and other lightweight data storage from one place to another, but alas, most people don’t have reliable access to carrier pigeons these days.

Sneakernet is a tongue-in-cheek term, but the actual concept is more commonly used than you might think, even with the growth of cloud storage.

Sneakernet’s value is in dealing with large volumes of data. For example, a 1TB removable hard drive is inexpensive and easily fits in a pocket or bag. 1TB is 1024GB, which is a little under 218 DVDs. At the median download speed in the UK, 1TB would take approximately 48 hours to download, assuming the internet wasn’t being used for anything else.

4TB or 5TB hard drives can also be purchased and are the same physical size. The amount of data that would fill one of these is often notably faster to transfer by ‘snail mail’ and that’s only for one removable hard drive. If you have more hard drives full of data, the time taken for transferring it across the internet is vastly increased, at 2 days per 1TB of data, while the physical drives are still conveniently portable.

In all seriousness, at Solidarity IT, when setting up backups or restoring data from them for our clients, we do offer the option of having hard drives sent by post, as for the reasons explained above, this can be the optimal method when large volumes of data are involved.