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This paper presents a comparison of three developmental experiences of fuzzy DBMS (Database Management Systems). These developments have expanded the functionality of some existing relational DBMS (PostgreSQL, Oracle, Firebird, SQL Server, MySQL and DB2) to handle queries with vague terms. The three approaches presented are based on three different methods of integration known as weak, medium and strong coupling strategies. These developments are based on evaluation mechanisms that give good behavior in terms of time spent for query processing. In addition, this paper also presents two user experiences of these fuzzy DBMS, which show a high acceptance by users. To do so, are some applications developed using our fuzzy DBMS. These experiences show that fuzzy DBMS are appropriate and necessary in real-world applications.

This paper investigates the use of the tools available in a Relational DBMS for the purpose of developing a Group Technology (GT) application. Specifically, we will concentrate on Structured Query Language (SQL) but the possibilities of using other features such as Host Language programming and Report Generators will also be examined. The paper demonstrates the use of Relational DBMS technology as a tool for implementing a GT project in an advanced manufacturing environment.

This note presents a translation of a subset of the relational query language SQL into the well known tuple calculus. Roughly speaking, tuple calculus corresponds to first order predicate calculus. The SQL subset is relationally complete and represents a “relational core” of the language. Nevertheless, our translation is simple and elegant. Therefore it is especially well suited as a beginners course into the principles of a formal definition of SQL.

Database management system (DBMS) products became the foundation for many (some say most) of the core applications in every industry, commercial business, and government agency. They became the engine that drove the sale of mainframe computers during the 1970s and for many years afterward. And yet their success was soon overtaken by relational DBMSs. One of the most interesting stories in the history of software products is how the new relational model, published in 1970 by E.F. (Ted) Codd, spawned a whole new set of independent software companies. Together with IBM, they developed the RDBMSs that supplanted the DBMS companies and their DBMS models in both query-oriented usage and in many transaction-processing applications. This Annals special issue tells the story of how this transformation began and describes how three companies pioneered the development of relational database management products to meet the relational challenge and build the foundation for the growth of a multibillion dollar industry.

We introduce the concept "team" and incorporate the team query into the data language SQL. Existing relational query languages use tuple variables of tables to specify required data. Queries that are expressed by these languages are used to get all the data which satisfy the specified conditions. While a team variable represents a subset of a table, a team query is used to retrieve all the teams that meet certain constraints. We introduce team qualifications and briefly describe team query processing. The search space of a team query may be very large. Therefore, instead of using conventional breadth-first search method, we adopt a depth-first search method for query processing. Thus, users can always get a result if one exists. >

Natural language (NL) interfaces for database query formulation have always been recognized as a much needed enhancement for end-users. Poor performances with earlier NL systems had led to a lull in research in this field. However, latter-day experiments and systems appear to be sufficiently more promising to warrant continued and further research in this area. This paper proposes an experimental query interface that filters NL query statements for search predicates that are derived from constructs on conceptual schemas, thereby avoiding the computational difficulty with full-fledged NL parsing. A prototype of the Conceptual Query Language (CQL) exists as a front-end to an Oracle relational DBMS.

In this paper, we study a simple SQL extension that enables query writers to explicitly limit the cardinality of a query result. We examine its impact on the query optimization and run-time execution components of a relational DBMS, presenting two approaches—a Conservative approach and an Aggressive approach—to exploiting cardinality limits in relational query plans. Results obtained from an empirical study conducted using DB2 demonstrate the benefits of the SQL extension and illustrate the tradeoffs between our two approaches to implementing it.

The relational model is a set-theoretic model for describing data constructs common in the business environment. Relational databases also minimize data duplication, which ensures data integrity and reduces storage requirements. Further, the relational model provides a way to represent variable-length constructs with fixed-length components. In addition, normalization theory is the basis of hundreds of papers and successful tenure applications. This ensured the academic community would carry the model forward. Finally, by following open standards, including the structured query language, vendors created a buzz with dozens of relational DBMS products such as System R, DB2, Oracle, SQL Server, Ingres, dBase, R:Base, Pearl, Paradox, and Access. An XDS have many advantages over a relational database, including seamless integration with user views as well as all the benefits of XML standards such as XML schema validation and the extensible stylesheet language for document materialization.

This paper discusses the advantages of using a large, relational database system in a database course and describes in detail a course that has been taught at UW Oshkosh using INGRES as a vehicle for instruction.

There is growing interest in abandoning the first-normal-form assumption on which the relational database model is based. This interest has developed from a desire to extend the applicability of the relational model beyond traditional data-processing application. In this paper, we extend one of the most widely used relational query languages, SQL, to operate on non-first-normal-form relations. In this framework, well allow attributes to be relation-valued as well as atomic-valued (e.g. integer or character). A relation which occurs as the value of an attribute in a tuple of another relation is said to be nested. Our extended language, called SQL/NF, includes all of the power of standard SQL as well as the ability to define nested relations in the data definition language and query these relations directly in the extended data manipulation language. A variety of improvements are made to SQL; the syntax is simplified and useless constructs and arbitrary restrictions are removed.

Recently, attention has been focused on temporal databases , representing an enterprise over time. We have developed a new language, Tquel , to query a temporal database. TQuel was designed to be a minimal extension, both syntactically and semantically, of Quel, the query language in the Ingres relational database management system. This paper discusses the language informally, then provides a tuple relational calculus semantics for the TQuel statements that differ from their Quel counterparts, including the modification statements. The three additional temporal constructs defined in Tquel are shown to be direct semantic analogues of Quel's where clause and target list. We also discuss reducibility of the semantics to Quel's semantics when applied to a static database. TQuel is compared with ten other query languages supporting time.

This paper describes a prototype DBMS, called VERTUR, which supports relational data structures and can be used inter-actively through a query language. The query language referred to as TURDIL is based on Turkish Language and is defined by a regular grammar. VERTUR has a fully integrated data dictionary which contains definitions of relations and user-views based on relations, along with information on data-access privileges.

The architectural design is presented of DATAPLEX, a heterogeneous distributed database management system, and a prototype DATAPLEX. The objective of DATAPLEX is to integrate existing diverse databases as well as emerging new databases within an organization for organization-wide date sharing and data consistency. The architecture of DATAPLEX is based on the relational data model as a common data model and the structured query language (SQL) as a standard query language. A method to decompose distributed queries in this architecture is developed. The prototype system interfaces an IMS hierarchical database management system (DBMS) on IBM/MVS and an INGRES relational DBMS on DEC/VMS. >

The relational database query language SQL (originally, "SEQUEL") was first developed as a non-procedural language: the user should specify only what data is desired, leaving it to the the system's query optimizer to determine how the data is accessed [ASTR 75]. IBM pioneered the development of query optimizer technology that would achieve this ideal, beginning with the well-known optimizer of System R [SELI 79], the prototype relational database management system (DBMS) developed at IBM Research Laboratory in San Jose, California during the late 1970's. The IBM products SQL/DS [SQL 84] and DB2 [CHEN 84], as well as the experimental distributed DBMS prototype R∗ [LOHM 85], contain optimizers that are based upon the System R prototype.

A database management system designed for instructional use should offer facilities usually not required in a commercial environment. One of the most important features desirable in such a system is its ability to perform query transformation. The use of an universal symbol and tree manipulation system to perform query translation, decomposition and optimization is described in the paper. Examples of transformation rules required to translate SQL expressions into equivalent QUEL expressions, decompose SQL expressions into parse trees and perform optimization of expressions based on relational algebra are shown.An experimental relational DBMS using the above approach is currently under development at the University of Houston. It supports various nonprocedural query languages within a single system, using a unified database dictionary. Cross-translation between various query languages is allowed. The results of every important phase of the query transformation during its execution are interactively available to the system user.

This paper presents a simple approach for extending the relational system INGRES into one supporting a semantic data model it describe a DBMS consisting of (i) a user-friendly front-end, supporting the GEM semantic data model and query language under the UNIX time-sharing system, and (ii) a dedicated back-end processor providing efficient support for database transactions, concurrency control and recovery GEM extends the relational model to support the notions of entities with surrogates, the relationships of aggregation and generalization, null values and set-valued attributes, and provides simple extensions of QUEL to handle these new constructs in this proposed implementation of GEM, the relational database processor IDM 500 by Britton-Lee is used as the back-end machine

This paper presents the preliminary design of a new database management system, called POSTGRES, that is the successor to the INGRES relational database system. The main design goals of the new system are to provide better support for complex objects, provide user extendibility for data types, operators and access methods, provide facilities for active databases (i.e., alerters and triggers) and inferencing including forward- and backward-chaining, simplify the DBMS code for crash recovery, produce a design that can take advantage of optical disks, workstations composed of multiple tightly-coupled processors, and custom designed VLSI chips, and make as few changes as possible (preferably none) to the relational model. The paper describes the query language, programming language interface, system architecture, query processing strategy, and storage system for the new system.

INGRES (Interactive Graphics and Retrieval System) is a relational data base and graphics system which is being implemented on a PDP-11/40 based hardware configuration at Berkeley. INGRES runs as a normal user job on top of the UNIX operating system developed at the Bell Telephone Laboratories. The only significant modification to UNIX that INGRES requires is a substantial increase in the maximum file size allowed. This change was implemented by the UNIX designers. The implementation of INGRES is primarily programmed in "C", a high level language in which UNIX itself is written. Parsing is done with the assistance of YACC, a compiler-compiler available on UNIX.