Data Compression in Shared Hosting
The ZFS file system which operates on our cloud Internet hosting platform employs a compression algorithm identified as LZ4. The aforementioned is substantially faster and better than any other algorithm you can find, especially for compressing and uncompressing non-binary data i.e. internet content. LZ4 even uncompresses data faster than it is read from a hard drive, which improves the overall performance of sites hosted on ZFS-based platforms. Because the algorithm compresses data quite well and it does that very quickly, we can generate several backups of all the content kept in the shared hosting accounts on our servers daily. Both your content and its backups will need less space and since both ZFS and LZ4 work very fast, the backup generation will not change the performance of the servers where your content will be kept.
Data Compression in Semi-dedicated Servers
The semi-dedicated server plans which we provide are created on a powerful cloud hosting platform that runs on the ZFS file system. ZFS works with a compression algorithm called LZ4 that surpasses any other algorithm available in terms of speed and compression ratio when it comes to processing web content. This is valid particularly when data is uncompressed as LZ4 does that more quickly than it would be to read uncompressed data from a hard disk and as a result, websites running on a platform where LZ4 is present will function faster. We're able to take advantage of the feature despite of the fact that it needs quite a large amount of CPU processing time as our platform uses a number of powerful servers working together and we don't create accounts on just a single machine like many companies do. There's another benefit of using LZ4 - since it compresses data very well and does that very fast, we can also generate several daily backup copies of all accounts without affecting the performance of the servers and keep them for a month. In this way, you will always be able to bring back any content that you delete by mistake.