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Why not use an existing database management system (DBMS) for storing scientific data? We looked at available database software, both commercial and research-oriented, and concluded that existing packages are currently inadequate for the kinds of scientific data access supported by the netCDF interface.
First, most existing DBMSs have poor support for multidimensional objects as the basic unit of data access. An alternative data model of comparable power and elegance to the relational model for databases is needed for scientific data. If such a model existed, programs that shared that model could be used in flexible combinations to support effective systems for building applications and visualizing data. Representing multidimensional arrays as relations makes some useful kinds of data access awkward and provides little support for the abstractions of multidimensional data and coordinate systems.
Related to this is a second problem with general-purpose database systems: their poor performance on large scientific data sets. Collections of satellite images, scientific model outputs, climate observations covering decades, high-resolution atmospheric profile data, and other large data sets are beyond the capabilities of most DBMSs to organize and index for efficient retrieval.
Finally, general-purpose database systems provide, at significant cost in terms of both resources and access performance, many facilities that are not needed in the analysis, management, and display of scientific data. For example, elaborate update facilities, concurrency control, audit trails, report writers, and mechanisms designed for transaction-processing are unnecessary for most scientific applications.
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