Backup and Archival Approaches
Let us first review the various backup/archival approaches for different needs and requirements. All approaches have pros and cons in regards to ease of restoring the data and the amount of memory needed for the scheme. One must select the appropriate backup approach based on the work pattern and type protection needed.
Note: If the backup/archival datasets are compressed for storage space reduction reason, it may be rendered useless if the decompression tool is not available when you need to restore.
Manual Backup picks which files need to be backed up. Time and space requirement for backup is very optimized, but is prone to human error and can miss backup cycles. It is also tedious to track of multiple generations.
Full Backup copies onto the backup medium the entire region to be protected. Subsequent backup cycles create another generation of backup set, preserving the prior set with a limit of how many generations are kept. When the maximum is reached, the oldest generation gets overwritten. Since all files are in one complete dataset, restoring process does not need to reconstruct the data. But the amount of time and space needed to hold an additional backup set is the same even if only a few files had been changed.
Incremental Backup starts with a Full Backup dataset. On subsequent cycles, backup only files that are changed since the previous cycle. Advantage of this method is it requires less time and space because subsequent sets only store the changed files of the previous dataset. But the restore logic must reconstruct the data set. First the Full Backup set is restored. Then, changes from subsequent backup cycles are restored until all subsequent cycles are restored. To minimize reconstruction, a full backup may be done again after so many incremental backup cycles. For example, 5-10 cycles.
Differential Backup starts with a Full Backup data set. Every cycle, the difference of what is on the computer versus the Full backup is saved. Only the Full Backup dataset and one subsequent dataset are needed to recreate a full dataset. The downside is subsequent difference dataset becomes larger and larger requiring more and more time and space.
In Continuous Data Protection, a Full Backup is created and subsequently any changes to any of the files protected are continuously recorded. Some CDP record a changed file when it is saved. Some record at finer granularity at each changed character or word. True-CDP records changes instantly. Near-CDP records changes at set time intervals. This method gives users choices of versions to restore. It is useful for data that constantly change such as word processing files, spread sheets, software source code, etc. But True-CDP at fine granularity requires much processing bandwidth to detect and backup the changes. Near-CDP requires much less bandwidth and is not OS invasive making it less affected by system upgrades or changes.
System backup (or Mirror) protects at the system level. A duplicate, complete dataset is kept on a similar device. Each change on the primary dataset is recorded in the mirror dataset instantly. Recovery does not need reconstruction, giving rise to High Availability (HA) configuration. Mirror device can instantly replace a failed primary device. This method needs specialized software and purpose-designed hardware.
System backup (Full PC Backup) is sometimes called bare metal backup. It clones the entire hard disk image (data + system) and hardware settings stored in the PC. When the PC failed, the stored info can be used to replicate the lost PC on a new one. This provides an easy way to restore a broken PC. But many dependencies and limitations exist. The new system must be the same as the old one to be able to accept the system setting. Deviations cause the restore to become useless.
Caltron Industries, Inc.
Supplier of data storage solutions.
4120 Clipper Court
Fremont, CA 94538
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