Object-oriented querying of existing relational databases

In this paper, we present algorithms which allow an object-oriented querying of existing relational databases. Our goal is to provide an improved query interface for relational systems with better query facilities than SQL. This seems to be very important since, in real world applications, relational systems are most commonly used and their dominance will remain in the near future. To overcome the drawbacks of relational systems, especially the poor query facilities of SQL, we propose a schema transformation and a query translation algorithm. The schema transformation algorithm uses additional semantic information to enhance the relational schema and transform it into a corresponding object-oriented schema. If the additional semantic information can be deducted from an underlying entity-relationship design schema, the schema transformation may be done fully automatically. To query the created object-oriented schema, we use the Structured Object Query Language (SOQL) which provides declarative query facilities on objects. SOQL queries using the created object-oriented schema are much shorter, easier to write and understand and more intuitive than corresponding S Q L queries leading to an enhanced usability and an improved querying of the database. The query translation algorithm automatically translates SOQL queries into equivalent SQL queries for the original relational schema

An Object-Oriented Language-Database Integration Model: The Composition-Filters Approach

This paper introduces a new model, based on so-called object-composition filters, that uniformly integrates database-like features into an object-oriented language. The focus is on providing persistent dynamic data structures, data sharing, transactions, multiple views and associative access, integrated with the object-oriented paradigm. The main contribution is that the database-like features are part of this new object-oriented model, and therefore, are uniformly integrated with object-oriented features such as data abstraction, encapsulation, message passing and inheritance. This approach eliminates the problems associated with existing systems such as lack of reusability and extensibility for database operations, the violation of encapsulation, the need to define specific types such as sets, and the incapability to support multiple views. The model is illustrated through the object-oriented language Sina

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database