Data Deduplication Overview

StorNext data deduplication refers to a specific approach to data reduction built on a methodology that systematically substitutes reference pointers for redundant variable-length blocks (or data segments) in a specific dataset. The purpose of data deduplication is to increase the amount of information that can be stored on disk arrays and to increase the effective amount of data that can be transmitted over networks.

For example, if the same 1 terabyte of file data appears in several different files, only one instance of that 1 terabyte needs to be retained. Each of those several files can use the same data bytes from a common storage source when the data is needed.

Quantum's deduplication not only recognizes duplicate data in the entire file, but also recognizes duplicate data ranges within files. For example, if two 1TByte files share the same data from byte 10,000,000 through byte 500,000,000, those duplicate byte ranges can be identified and stored only once. Several files may contain the same data or some of the same data, and these files can all benefit from deduplication.