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Database cloning is the process by which a copy of an existing database system is made.  It is a best practice adopted by database administrators and other professionals. An example use case would be  a copy of the production database cloned for development testing, or reporting, or  simply for backup. Another example would be a QA environment where a need  arises to restore an environment to a specific point in time to perform testing. The cloning process is generally tedious, time consuming, and subject to errors. The Pure Storage FlashArray comes with snapshotting capability that users can leverage for a variety of purposes, including cloning databases quickly and easily.

Data reduction is a capacity optimization technique in which data is reduced to its simplest possible form to free up capacity on a storage device. There are many ways to reduce data, but the idea is very simple—squeeze as much data into physical storage as possible to maximize capacity.

A relational database management system (RDBMS) is a tool for managing databases that use the relational model of data storage in which structured data is stored in tables consisting of rows and columns.

Relational databases come with a number of advantages:

• Ability to quickly access specific data via fast SQL queries 

• Ubiquity of tools, technologies, and expertise for working with relational databases

• Atomicity, Consistency, Isolation, Durability (ACID) compliance

Volume snapshots in Pure Storage Data Services are immutable, point-in-time images of the contents of one or more volumes. Volume snapshots can be created individually or as a part of a protection group. A protection group ensures that the snapshots created of volumes within it are consistent with one another.  Volume snapshots are always thin-provisioned, deduplicated, compressed and require no snapshot capacity reservations. All volumes (and by extension snapshots) are thin provisioned and a part of a global deduplication namespace, further reducing the storage space consumed. With snapshots as the data movers in the data fabric, it reduces data sprawl, silos and it can all be easily automated.