Automation everywhere: Autonomics and data management

Traditionally, database management systems (DBMSs) have been associated with high-cost, high-quality functionalities. That is, powerful capabilities are provided, but only in response to careful design, procurement, deployment and administration. This has been very successful in many contexts, but in an environment in which data is available in increasing quantities under the management of a growing collection of applications, and where effective use of available data often provides a competitive edge, there is a requirement for various of the benefits of a comprehensive data management infrastructure to be made available with rather fewer of the costs. If this requirement is to be met, automation will need to be deployed much more widely and systematically in data management platforms. This paper reviews recent results on autonomic data management, makes a case that current practice presents significant opportunities for further development, and argues that comprehensive support for automation should be central to future data management infrastructures. © Springer-Verlag Berlin Heidelberg 2007.