Two kinds of abstraction that are fundamentally important in database design and usage are defined. Aggregation is an abstraction which turns a relationship between objects into an aggregate object. Generalization is an abstraction which turns a class of objects into a generic object. It is suggested that all objects (individual, aggregate, generic) should be given uniform treatment in models of the real world. A new data type, called generic, is developed as a primitive for defining such models. Models defined with this primitive are structured as a set of aggregation hierarchies intersecting with a set of generalization hierarchies. Abstract objects occur at the points of intersection. This high level structure provides a discipline for the organization of relational databases. In particular this discipline allows: (i) an important class of views to be integrated and maintained; (ii) stability of data and programs under certain evolutionary changes; (iii) easier understanding of complex models and more natural query formulation; (iv) a more systematic approach to database design; (v) more optimization to be performed at lower implementation levels. The generic type is formalized by a set of invariant properties. These properties should be satisfied by all relations in a database if abstractions are to be preserved. A triggering mechanism for automatically maintaining these invariants during update operations is proposed. A simple mapping of aggregation/generalization hierarchies onto owner-coupled set structures is given.

The design and motivation for a rotating associative relational store (RARES) is described. RARES is designed to enhance the performance of an optimizing relational query interface by supporting important high level optimization techniques. In particular, it can perform tuple selection operations at the storage device and also can provide a mechanism for efficient sorting. Like other designs for rotating associative stores, RARES contains search logic which is attached to the heads of a rotating head-per-track storage device. RARES is distinct from other designs in that it utilizes a novel “orthogonal” storage layout. This layout allows a high output rate of selected tuples even when a sort order in the stored relation must be preserved. As in certain other designs, RARES can usually output a tuple as soon as it is found to satisfy the selection criteria. However, relative to these designs, the orthogonal layout allows an order of magnitude reduction in the capacity of storage local to the search logic.

There are significant advantages to tailoring hardware storage devices to support high level data models in very large data bases. A storage device that can assume some of the data selection functions traditionally performed by the CPU can substantially reduce the amount of data to be transferred to the CPU. This reduction together with increased concurrency of CPU and device operation result in increased data rates and lowor response times By designing the device to support one specific data model, greator efficiency can be achieved than in devices dosigned to be a compromise in their support of several different models. The number and complexity Of the functions performed by the device can be drastically reduced, along with its development and production costs. In this paper we describe the design and usage Of an associative array memory using a rotating storage device which is tailored to support the relational model of E. F. Codd.