File Systems simplify storing and organizing data.  But they often cause significant performance loss.  For instance, while ZFS is impressive in terms of its convenience, scale, and data reliability, the interior design reduces random write throughput from gigabytes to megabytes per second.  Similarly, ZFS uses a B-tree to organize access to data.  B-tree usage in a terabyte storage environment requires about 15 reads merely to access the location of data. Many of these are "real reads" rather than reads from storage media.  This profoundly slows down read rates.

WFFS - short for WildFire File System - is designed to overcome the performance issues inherent in most file systmes while achieving the reliability, flexibility, and scale expected of the best and most reliable file systems.

WildFire has already demonstrated a high performance block product: ESS - Enterprise Storage Stack.  ESS converts clusters of random writes into linear writes.  As a result, it inherently writes at the composite linear write rate of the SSDs present.  Similarly, ESS can update both regular and SMR hard disks at their linear write speed.

ESS by itself does not improve reads.  But it reduces read amplification.  For instance, when fully memory mapped, ESS performs one memory read per data block read.  When using third party file systems such as ZFS, XFS, NTSF, and so forth, both ESS ans WFFS can maximize the performance of these.  But when WFFS is the primary file system, it can dramatically increase read performance by as much as ten-fold because the ten to twenty reads of a b-tree based read-access can be replaced with one to three hash-based reads.

There are other ways of attaining efficiency in file systems.  For instance, on the one hand, memory virtualization can reduce memory requirements by a factor of 10.  Hashing can be used to reduce named file and directory lookups to just two or three per actual read.  Similarly, by requiring that all writes to hard disks be "big", while sending all "small" writes to flash it's possible to use hard disks only where they are most efficient: with large sized files.