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Technical Insight: Data Reduction Estimator

Data reduction has become prevalent in flash storage systems and even though there are some variations in implementation, the reduction of data represents economic value by requiring less physical capacity. The challenge for acquiring all flash storage systems is arriving at a correctly sized system given the workloads and associated data that will be stored. Purchasing too little can lead to problems both in making another acquisition with the immediacy required when running out of space and the impacts of having to make an additional purchase that is off-cycle with the appearance of poor-planning. Purchasing too large a system with more capacity than is required not only makes the purchase price higher than necessary, it does not allow taking advantage of the continued price reductions for flash storage over time by buying additional capacity when required.

Data reduction includes data compression and data deduplication. Compression can yield fairly consistent results for given types of data. Data deduplication is effective when there is repeated data such as with successive backups and with virtual desktops where layering was not utilized. Some flash storage systems offer both while others focus on consistent gains from data compression. This data reduction estimator is based on using both but it should be understood that the type of data determines which reduction technology is the most effective.

The Data Reduction Estimator is useful for planning the capacity of the flash storage system that is being acquired. It is a guide based on expected data from a history of data types. A number of vendors offer guarantees for their data reduction effectiveness, which are useful in removing risk. The calculator can give an expectation, which is the best information available before actually deploying a system or running lengthy software analysis on the actual data to be stored. The calculator tool is available at

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Related to this document:
NAS Evaluation Guide, SAN Performance Concepts 101, Data De-Duplication –Why, When Where and How? — InfoStor Article by Russ Fellows

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August 8, 2016

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