OLAP users have no
alternative but to analyse stale data.
But a decision support system that could provide decision makers insight into up-todate
data ???hot off the press??? would open exciting new possibilities. A stockbroker,
for example, could analyse current trends in the market online. For e-commerce, the
personalisation of Web shops could be much improved by more complex analysis of
current browsing behaviour. Even for the so-called ???old economy,??? new perspectives
open up, because the update window has already become drastically small in a 24/7
setting of a worldwide operating company. However, up to now there is no solution
that meets these performance and freshness requirements at the same time.
In this chapter, we present a new approach to online decision support systems
that is capable of analysing up-to-date data. It is based on a database cluster: this
is a cluster of commercial off-the-shelf computers as hardware infrastructure and
off-the-shelf database management systems as transactional storage managers. A
coordination middleware on top hides the details and provides a uniform, generalpurpose
query interface. The result is a ???database of databases??? following the vision
of a hyperdatabase (Schek, B?¶hm, Grabs, R?¶hm, Schuldt, & Weber, 2000). An
important design principle of a database cluster is its component-oriented nature.
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