Data persistence is a basic building block of almost any software system - applications need to save and retrieve data. Last year marked the 30th anniversary of the commercial RDMBS, a technology that has been with us for most of our working lives, and has - in a way similar to how ducklings imprint on their mother - shaped our thinking about how modern, general computer programs deal with data persistence.

Today, however, as we stumble forward into the era of "cloud" computing, the various architectures that fall under the cloud umbrella - ranging from resource provisioning and service components of Amazon's AWS to richer service platforms like Google's App Engine to large-scale consumer-facing systems like Facebook - all work on a scale in which the classic RDBMS, if even present, is stretched past the limits of its capabilities as requirements for size, reliability, and geographic span pit these solutions against the constraints of technology and physics.

Fortunately, new persistence technologies are being developed, providing developers and architects with new "ingredients" with which to build systems, both large and small. These new technologies are fundamentally different than the RDMS systems that many to most of us are familiar with, and these differences require us to change how we model and manage our data. This talk provides an overview of some of these new data persistence technologies, and shows how these technologies are going to let developers rethink how they design, deploy and manage the data for their applications.