A much-touted advantage of the relational data model is the existence of a formal calculus and algebra to model database queries. In practice, these formalisms fail to model many of the features present in commercial query languages (e.g., SQL): grouping, aggregation, duplicate values, and sort orders. The gap only widens as one moves to object- oriented query languages, such as OQL of ODMG-93, which must deal with multiple bulk (collection) types, arbitrary nesting of type constructors, methods and embedded query expressions. Such features also appear in relational query language standards proposals, such as SQL3. This work addresses efficient query processing for modern database languages. It seeks to demonstrate through prototype implementation that new language features can be handled more effectively if these features have direct support in a query calculus. The research framework is based on such a calculus, called the monoid comprehension calculus. Instead of starting from relational algebra and making extensions, our formal model represents naturally the new emerging features of database lang uages. A successful outcome for the research will lead to a better basis for implementing the query processors of commercial database systems, both of pure object-oriented models and relational-object
