DB2 Design Advisor

Zilio, Daniel; Rao, Jun; Lightstone, Sam; Lohman, Guy M.; Storm, Adam; Garcia-Arellano, Christian; Fadden, Scott

doi:10.1016/b978-012088469-8.50095-4

Cited by 103 publications

(1 citation statement)

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“…L. Haas From a systems research perspective, there are several approaches one might take to this challenge. Perhaps the simplest is to start by building an "Integration Advisor", on the model of today's physical design advisors [49,50]. This tool would lead the user through the various integration steps, asking for input on the desiderata, and then recommend the appropriate engines, and perhaps even generate the configuration information needed.…”

Section: The "Big I" Challengementioning

confidence: 99%

Beauty and the Beast: The Theory and Practice of Information Integration

Haas

2006

Lecture Notes in Computer Science

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Abstract. Information integration is becoming a critical problem for businesses and individuals alike. Data volumes are sky-rocketing, and new sources and types of information are proliferating. This paper briefly reviews some of the key research accomplishments in information integration (theory and systems), then describes the current state-of-the-art in commercial practice, and the challenges (still) faced by CIOs and application developers. One critical challenge is choosing the right combination of tools and technologies to do the integration. Although each has been studied separately, we lack a unified (and certainly, a unifying) understanding of these various approaches to integration. Experience with a variety of integration projects suggests that we need a broader framework, perhaps even a theory, which explicitly takes into account requirements on the result of the integration, and considers the entire end-to-end integration process.

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Section: The "Big I" Challengementioning

confidence: 99%

Beauty and the Beast: The Theory and Practice of Information Integration

Haas

2006

Lecture Notes in Computer Science

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Autonomics and data management

Paton

2008

Concurrency and Computation

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SUMMARYTraditionally, database management systems 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 successful in many contexts, but in an environment in which data are available in increasing quantities under the management of a growing collection of distributed applications, and where effective use of available data often provides a competitive edge, there is a requirement for various 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, whether centralized or distributed.

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