Databases are evolving faster than ever, becoming more fluid to keep pace with an online world that's becoming virtualized at every level.

In many ways, the database as we know it is disappearing into a virtualization fabric of its own. In this emerging paradigm, data will not physically reside anywhere in particular. Instead, it will be transparently persisted, in a growing range of physical and logical formats, to an abstract, seamless grid of interconnected memory and disk resources; and delivered with subsecond delay to consuming applications.

Real-time is the most exciting new frontier in business intelligence, and virtualization will facilitate low-latency analytics more powerfully than traditional approaches. Database virtualization will enable real-time business intelligence through a policy-driven, latency-agile, distributed-caching memory grid that permeates an infrastructure at all levels.

As this new approach takes hold, it will provide a convergence architecture for diverse approaches to real-time business intelligence, such as trickle-feed extract transform load (ETL), changed-data capture (CDC), event-stream processing and data federation. Traditionally deployed as stovepipe infrastructures, these approaches will become alternative integration patterns in a virtualized information fabric for real-time business intelligence.

The convergence of real-time business-intelligence approaches onto a unified, in-memory, distributed-caching infrastructure may take more than a decade to come to fruition because of the immaturity of the technology; lack of multivendor standards; and spotty, fragmented implementation of its enabling technologies among today's business-intelligence and data-warehouse vendors. However, all signs point to its inevitability.

Case in point: Microsoft, though not necessarily the most visionary vendor of real-time solutions, has recently ramped up its support for real-time business intelligence in its SQL Server product platform. Even more important, it has begun to discuss plans to make in-memory distributed caching, often known as "information fabric," the centerpiece middleware approach of its evolving business-intelligence and data-warehouse strategy.