Since computers were introduced to automate organization management,
information system evolution has influenced data management considerably.
Applications demand more and more services from information stored in
computing systems. These new services impose more stringent conditions on
the currently prevailing client/server architectures and relational database
management systems (DBMSs). For the purpose of this book, those
demands can be arranged along three aspects, namely:
Enhancements on the structural side. The tabular representation of data
has proved to be suitable for applications, such as insurance and banking,
that have to process large volumes of well-formatted data. However, newer
applications such as computer-aided manufacturing or geographic information
systems have a tough job attempting to fit more elaborate structures into
flat records. Moreover, the SQL’92 types are clearly insufficient to tackle
time or multimedia concerns.
Improvements on the behavioral side. Data are no longer the only aspect
to be shared. Code can, and must, be shared. DBMS providers are striving to
make their products evolve from data servers to code servers. The introduction
of rules to support active and deductive capabilities and the inclusion of
user-defined data types are now part of that trend.
Architectural issues. New applications need access to heterogeneous and
distributed data, require a higher throughoutput (e.g., large number of transactions
in e-commerce applications), or need to share code. The client/server
architecture cannot always meet those new demands.
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