Data efficiency is maximized in a PowerStore array by using integrated data deduplication and data compression features. Built with modern Intel Xeon processors, the PowerStore array is designed for low-overhead, always-on data deduplication, and compression. These data reduction technologies have no perceptible impact on storage performance. Both data reduction features are always on for the array and cannot be disabled by storage administrators.

Data deduplication is a technology that identifies redundancies in the data that is stored on the system. PowerStore uses an efficient system of storage location “pointers” so that multiple volumes can reference a single copy of the redundant data. Data deduplication saves space. The process of detecting and managing data deduplication occurs before the data is written to the storage systems. This results in fewer write I/O operations as compared to deduplication methods that periodically scan the data after it has been written to disk. Benefits of data deduplication include:

• Inline deduplication minimizes the rate of storage capacity that is needed for data growth and extends a customer’s investment.
• Reducing writes associated with redundant data improves drive endurance.
• Consuming cache only for unique data improves performance.

Data compression is the process of reducing the size of data that is stored to the system by implementing a more compact representation without losing information content. Customers gain additional value from PowerStore when the system can efficiently store more data on fewer blocks. Like deduplication, compression also reduces the number of write operations to the storage drives which increase both reliability and performance.

Storage administrators can easily track the physical capacity use (used and free space) and Data Savings statistics in the PowerStore Manager dashboard under the Capacity tab. Data Savings metrics are global for the array, which means that the overall efficiency, space savings, and space savings ratio apply to everything on the storage system.

Note: An important point to remember when reviewing the data savings results in this paper is that all results are reported at the global storage system level and not for individual databases or LUNs.