If you’ve worked with a database for a while, you probably have heard of purging, archiving, and deleting data. Although some of the terms are used interchangeably, there are enormous differences between them.
Archiving Data
Database archiving is the process of moving historical data from production environments to an archive environment, freeing up IT storage space and other resources. Unlike database backup, database archiving should be leveraged for data that still has business value, but is infrequently accessed on the production environment.
It is an excellent approach to reduce hardware, storage, and maintenance costs of enterprise applications. It also increases application performance and streamlines back-ups and application upgrades.
Purging Data
When a table row in a database exceeds several hundred or millions of records that are no longer needed, database administrators know it is time to purge. Even though they move the records from a large table to an archive table, the data is not deleted. This process not only frees up space, it also speeds up queries.
Deleting Data
If you delete information, it is permanently removed from a table. Bear in mind that this task doesn't keep a copy of the records and it should only be performed by the administrator. This method can be also used to keep a server working efficiently and to free disk space. Administrators can also delete databases that are no longer active.
Differences Archiving, Purging and Deleting Data
The main difference between these types of administration techniques is that purging keeps a copy of the data and this is more beneficial when removing large amounts of records. If the admin only needs to remove one record, deleting takes fewer resources on the database server, so in comparison, it is faster than purging. Purging is generally used on large record sets and deleting is used on a small number of rows. On the other hand, archiving captures and stores historical data in its original business context based on business rules and definitions. Also, it maintains the referential integrity of the archived data, ensuring long-term, application-independent access to archived data via multiple access methods, including third-party reporting tools.
Storing large volumes of data has reached a critical point. Companies once only handled megabytes and gigabytes, and they now manage terabytes and petabytes of data and storage. We know there is a finite amount of storage available to save those bits and bytes.
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