Data Compression in Shared Hosting
The ZFS file system which runs on our cloud web hosting platform employs a compression algorithm named LZ4. The latter is considerably faster and better than every other algorithm out there, particularly for compressing and uncompressing non-binary data i.e. internet content. LZ4 even uncompresses data faster than it is read from a hard disk, which improves the performance of Internet sites hosted on ZFS-based platforms. Because the algorithm compresses data quite well and it does that quickly, we're able to generate several backup copies of all the content kept in the shared hosting accounts on our servers daily. Both your content and its backups will require less space and since both ZFS and LZ4 work extremely fast, the backup generation will not change the performance of the hosting servers where your content will be kept.
Data Compression in Semi-dedicated Hosting
The semi-dedicated hosting plans which we provide are created on a powerful cloud hosting platform that runs on the ZFS file system. ZFS employs a compression algorithm known as LZ4 that is better than any other algorithm available in terms of speed and data compression ratio when it comes to processing website content. This is valid especially when data is uncompressed as LZ4 does that more rapidly than it would be to read uncompressed data from a hard disk and because of this, sites running on a platform where LZ4 is present will work quicker. We're able to take advantage of the feature although it needs quite a great deal of CPU processing time because our platform uses a number of powerful servers working together and we never create accounts on a single machine like many companies do. There's another benefit of using LZ4 - considering that it compresses data rather well and does that speedily, we can also make several daily backups of all accounts without affecting the performance of the servers and keep them for a whole month. By doing this, you will always be able to bring back any content that you erase by mistake.