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An object-based system can determine if any changes to a file or its attributes have occurred since it was last backed up. If modifications are detected, only the changes are backed up--not the entire file. This can eliminate the unnecessary copying of large amounts of data, thus significantly speeding up backups and reducing the amount of storage space required.
Hashing and storage
Hashing algorithms--one of the key components of object-based storage--were developed in academic computing circles decades ago and are widely used in computer security, encryption and authentication technologies. With hashing, a string of data is analyzed to produce a unique value, or signature, that identifies the original segment of data. In security systems, hashing algorithms are commonly used in public-key
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In object-based storage, hashing algorithms are used similarly to uniquely identify segments of data that are stored in file systems. Incoming data files are parsed into uniformly sized objects and a hash value is calculated for each one. The results are then compared to those in an existing hash index, which is essentially a database that holds the hash values--or meta data--for each data segment. If an identical hash value already exists in the index, then the piece of data it represents isn't copied (backed up). If the new hash value doesn't match any in the hash index, it's added to the index and the associated data object is copied into the object-based environment.
| Traditional backup is storage-intensive |
This was first published in May 2004
Storage Management Strategies for the CIO

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