Since one of the critical factors in any backup is the amount of data that has to be moved, a solution for limiting this amount should be looked for. The best way to do this is to back up changes only.
The incremental pattern has no knowledge of a full backup. The first backup will be an incremental that will back up everything (so, essentially the same as a full backup). Afterwards however, only incremental backups need to be taken.
It is clear that this pattern will limit the amount of backed up data, but turns tape management and usage into a very complex process. That is why you will need a backup application that is capable of managing these tapes.
A good example of this is tape reusage. Since there is no determined point in time where tapes can be reused (as we had in the previous two patterns), the number of tapes can increase dramatically. Therefore, the application should be able to check tapes and clean them if necessary. This cleanup (or tape reclamation ) should occur when a tape holds backup data that will no longer be used, since newer versions have been backed up.
Another point is that when backing up data from different machines, their data can be dispersed over a multitude of different tapes. Since mounting a tape is a slow process, this should be avoided. That's why some applications have a mechanism that is called collocation . Collocation will try to maintain the data of one machine on the fewest number of tapes possible.
This should mean a performance gain when restoring, but will slow down the backup (we have, for example, a backup server with one tape drive, so only one tape can be mounted at a time, but two different machines try to back up at the same time). Instead of moving the backup data of both clients to the same tape, the backup program will try to put the data of both clients on separate tapes. Therefore, the second client will have to wait until the backup of the first one completes before it can start its backup. Again, applications have been provided by mechanisms to limit the impact of this (see Hierarchical Storage).
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