Database High Availability: An Extended Survey

Database High Availability: An Extended Survey

Moh’d A. Radaideh (Abu Dhabi Police – Ministry of Interior, United Arab Emirates) and Hayder Al-Ameed (United Arab Emirates University, United Arab Emirates)
Copyright: © 2009 |Pages: 23
DOI: 10.4018/978-1-60566-098-1.ch027


With the advancement of computer technologies and the World Wide Web, there has been an explosion in the amount of available e-services, most of which represent database processing. Efficient and effective database performance tuning and high availability techniques should be employed to insure that all e-services remain reliable and available all times. To avoid the impacts of database downtime, many corporations have taken interest in database availability. The goal for some is to have continuous availability such that a database server never fails. Other companies require their content to be highly availabile. In such cases, short and planned downtimes would be allowed for maintenance purposes. This chapter is meant to present the definition, the background, and the typical measurement factors of high availability. It also demonstrates some approaches to minimize a database server’s shutdown time.
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Needs For Engineering Information Modeling

Complex Objects and Relationships

Engineering data have complex structures and are usually large in volume. But engineering design objects and their components are not independent. In particular, they are generally organized into taxonomical hierarchies. The specialization association is the well-known association. Also the part-whole association, which relates components to the compound of which they are part, is another key association in engineering settings.

In addition, the position relationships between the components of design objects and the configuration information are typically multi-dimensional. Also, the information of version evolution is obviously time-related. All these kinds of information should be stored. It is clear that spatio-temporal data modeling is essential in engineering design (Manwaring, Jones, & Glagowski, 1996).

Typically, product modeling for product family and product variants has resulted in product data models, which define the form and content of product data generated through the product lifecycle from specification through design to manufacturing. Products are generally complex (see Figure 1, which shows a simple example of product structure) and product data models should hereby have advanced modeling abilities for unstructured objects, relationships, abstractions, and so on (Shaw, Bloor, & de Pennington, 1989).

Figure 1.

An example illustration of product structure


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