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Journal ArticleDOI

Federated database systems for managing distributed, heterogeneous, and autonomous databases

Amit P. Sheth, +1 more
- 01 Sep 1990 - 
- Vol. 22, Iss: 3, pp 183-236
TLDR
In this paper, the authors define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed, and define a methodology for developing one of the popular architectures of an FDBS.
Abstract
A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.

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Citations
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Journal ArticleDOI

Heterogeneous and autonomous transaction processing

TL;DR: The authors regard the three dimensions of HATP as independent, and they present concrete design and implementation techniques to support this view.
Journal ArticleDOI

A Survey on Geographically Distributed Big-Data Processing using MapReduce

TL;DR: In this paper, the authors investigate and discuss challenges and requirements in designing geographically distributed data processing frameworks and protocols and classify and study batch processing, stream processing, and SQL-style processing geo-distributed frameworks, models, and algorithms with their overhead issues.
Journal ArticleDOI

The metadatabase project at Rensselaer

TL;DR: The metadatabase model emcompasses the generic tasks of heterogeneous, distributed, aand autonomous databases administration, but also includes information resources management and integration of concurrent (functional) systems.
Book ChapterDOI

Tracing Data Lineage Using Automed Schema Transformation Pathways

TL;DR: Automed is a database transformation and integration system supporting both virtual and materialized integration of schemas expressed in a variety of modelling languages, and a set of primitive schema transformations operate on HDM schemas.
Journal ArticleDOI

A query processing algorithm for a system of heterogeneous distributed databases

TL;DR: This paper presents a query processing algorithm, formulated and developed in support of the prototype architecture of the Distributed Access View Integrated Database (DAVID), which is a heterogeneous distributed database management system.
References
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Book

The entity-relationship model: toward a unified view of data

TL;DR: A data model, called the entity-relationship model, is proposed that incorporates some of the important semantic information about the real world and can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model.
Book

Fundamentals of Database Systems

TL;DR: Fundamentals of Database Systems combines clear explanations of theory and design, broad coverage of models and real systems, and excellent examples with up-to-date introductions to modern database technologies.
Book

An Introduction to Database Systems

C. J. Date
TL;DR: Readers of this book will gain a strong working knowledge of the overall structure, concepts, and objectives of database systems and will become familiar with the theoretical principles underlying the construction of such systems.
Book

Principles of Distributed Database Systems

TL;DR: This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels and concentrates on fundamental theories as well as techniques and algorithms in distributed data management.
Journal ArticleDOI

A comparative analysis of methodologies for database schema integration

TL;DR: The aim of the paper is to provide first a unifying framework for the problem of schema integration, then a comparative review of the work done thus far in this area, providing a basis for identifying strengths and weaknesses of individual methodologies, as well as general guidelines for future improvements and extensions.
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