When you think of database virtualization, do you think this term means:

a) Abstracting the database installation/engine from the application and storage layers.
b) Abstracting the database instance across multiple database installations or engines.
c) Abstracting the data and tables from a specific database engine/type, to make the dependent application interfaces more generic.
d) Abstracting the data and tables across multiple database installations/engines.
e) Moving your database to the cloud.
f) All of the above.

I took a ‘staycation’ last month, hanging around the house to do some spring cleaning. Part of the cleaning process was cutting through the pile of unread technical magazines and trade rags to see if there was anything interesting before I threw them into the garbage. I probably should have just thrown them all away, as in the half dozen articles I read on the wonderful things database virtualization can do for you, not one offered a consistent definition. In most cases, the answer was f), and they used the term “database virtualization” to mean all of the above options with actually mentioning that database virtualization can have more than one definition. One particularly muddled piece at eWeek last October used all of the definitions interchangeably – within a single article.

Databases have been using abstraction for years. Unfortunately the database techniques are often confused with other forms of platform, server, or application virtualization – which run on top of a hypervisor utilizing any of several different techniques (full, emulated, application, para-virtualization, etc.). To further confuse things, other forms of abstraction and object-relational mapping layers within applications which uses the database, do not virtualize resources at all. Let’s take a closer look at the options and differentiate between them:

a) This form of database virtualization is most commonly called “database virtualization”. It’s more helpful to think about it as application virtualization because the database is an application. Sure, the classic definition of a database is simply a repository of data, but from a practical standpoint databases are managed by an application. SQL Server, Oracle and MySQL are all applications that manage data.
b) This option can also be a database virtualization model, We often call this clustering, and many DBAs will be confused if you call it virtualization. Note that a) & c) are not mutually exclusive.
c) This is not a database virtualization model, but rather and abstraction model. It is used to decouple specific database functions from the application, as well as enabling more powerful 4GL object-oriented programming rather than dealing directly with 3GL routines and queries. The abstraction is handled within the application layer through a service like Hibernate, rather than through system virtualization software like Xen or VMware.
d) Not really database virtualization, but abstraction. Most DBAs call this ‘partitioning’, and the model has been available for years, with variants from multiple database vendors.
e) The two are unrelated. Chris Hoff summarized the misconception well when he said “Virtualization is not a requirement for cloud computing, but the de-facto atomic unit of the digital infrastructure has become the virtual machine”. Actually, I am paraphrasing from memory, but I think that provides the essence of why people often equate the two.

This is important for two reasons. One, the benefits that can be derived depend heavily on the model you select. Not every benefit is available with every model, so these articles are overly optimistic. Two, the deployment model affects security of the data and the database. What security measures you can deploy and how you configure them must be reconsidered in light of the options you select.