Data compression is the compacting of data by lowering the number of bits which are stored or transmitted. Thus, the compressed data will need less disk space than the original one, so much more content can be stored on identical amount of space. There're many different compression algorithms that work in different ways and with a number of them only the redundant bits are removed, therefore once the data is uncompressed, there's no decrease in quality. Others remove unnecessary bits, but uncompressing the data following that will lead to reduced quality compared to the original. Compressing and uncompressing content needs a large amount of system resources, especially CPU processing time, so each and every Internet hosting platform that employs compression in real time must have sufficient power to support this attribute. An example how info can be compressed is to substitute a binary code such as 111111 with 6x1 i.e. "remembering" what number of sequential 1s or 0s there should be instead of keeping the whole code.

Data Compression in Shared Hosting

The compression algorithm that we work with on the cloud web hosting platform where your new shared hosting account will be created is known as LZ4 and it is applied by the state-of-the-art ZFS file system which powers the platform. The algorithm is far better than the ones other file systems use as its compression ratio is a lot higher and it processes data considerably faster. The speed is most noticeable when content is being uncompressed since this happens faster than info can be read from a hard drive. As a result, LZ4 improves the performance of each Internet site stored on a server that uses this algorithm. We take advantage of LZ4 in one more way - its speed and compression ratio make it possible for us to produce multiple daily backups of the entire content of all accounts and store them for one month. Not only do these backups take less space, but in addition their generation won't slow the servers down like it can often happen with many other file systems.