Data Virtualization in the Cloud Era

Chapter 2. Recent Technology Developments Driving the Rebirth of Data Virtualization

For decades, both well-known research projects in academia and small and large software vendors in industry have sold the promise of data virtualization. In almost every case, these projects fell short of the promise, stigmatizing the industry associated with the terms data virtualization and data federation. 

It’s not that they could not do what they set out to do—every project produced an interface that could query data from various sources. The problem was that each solution came with side effects that undermined the utility of the solution. Some examples of such side effects are: 

• The performance is too slow.

• The solution is too hard to use.

• The solution is too narrow because it only works for specific types of data or underlying data storage solutions.

In this chapter, we will explore the fundamentals of data virtualization: what makes it hard and what are the challenges in building such systems? Why exactly have many systems fallen short of their promise? 

Then we will discuss some recent technology developments that offer an optimistic outlook that data virtualization may succeed in areas where it has previously failed. These technology developments are independent of any one software vendor. Rather, every vendor in the data virtualization space can take advantage of these developments. 

Definitions

Throughout this book, we will refer to the software that implements a data virtualization ...