StoneFusion – a patented network operating system loaded on all of the Storage solutions of StoneFly, Inc is enriched with data deduplication technology useful for increased storage efficiency. It allows users to fit 5x to 137x more data within the same storage footprint with minimal impacts to overall performance. Block segmentation optimizes efficiency based on data type. Thus, by reducing storage capacity, organizations will enjoy related cost reductions in areas including storage licensing, storage management, power, cooling and data center floor space.
StoneFly’s dedup operates mostly outside the data path of the storage application software as a duplicate advisory service. Since, StoneFusion dedup offers parallel deduplication, higher write latencies usually observed in in-line deduplication are greatly reduced. It has the capability to handle heavy workloads and so can rapidly identify duplicate data across Terabytes of data.
How StoneFly’s deduplication works?
StoneFusion propelled deduplication uses memory resident information over 99% of the time, avoiding costly disk access and eliminates the largest single bottleneck in storage deduplication. As a first step, the operating system starts pushing new data and internal placement info to be deduplicated. Then block-aware segmentation breaks larger objects into variable sized chunks and then unique content fingerprints are computed. As soon as this process is completed, patented indexing technologies start the process of determining if the chunk has been previously seen. Previous placement information is pushed asynchronously back to the StoneFusion operating system for unification.
Independent validation has demonstrated that StoneFly’s deduplication software offers up to 7x data reduction for general purpose environments and up to 137x for virtualized images such as those generated by VMware. This helps in greatly reducing storage footprint along with all of the operating expenses involved.
Therefore, StoneFusion offered data deduplication has the potential to deliver substantial and recurring impact on the cost and manageability of data growth.