364 research outputs found

    Schema architecture and their relationships to transaction processing in distributed database systems

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    We discuss the different types of schema architectures which could be supported by distributed database systems, making a clear distinction between logical, physical, and federated distribution. We elaborate on the additional mapping information required in architecture based on logical distribution in order to support retrieval as well as update operations. We illustrate the problems in schema integration and data integration in multidatabase systems and discuss their impact on query processing. Finally, we discuss different issues relevant to the cooperation (or noncooperation) of local database systems in a heterogeneous multidatabase system and their relationship to the schema architecture and transaction processing

    A Framework for Flexible Transaction Management in Multidatabase Systems

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    The Issues And Solutions Of Integrating DBMS To A Multi-DBMS

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    Many organizations invest heavily in heterogeneous databases according to organizational functions. These heterogeneous databases are stand-alone systems that do not interact with one another. The objective of this paper is to introduce a multi-database system (MDBMS) that interacts with other heterogeneous DBMS within the organization to integrate information processing. In this paper, we discuss the potential inconsistencies in integrating heterogeneous databases. We further extend to include issues in designing a MDBMS. With a MDBMS, data sharing across organization reduces overheads and costs, thus, provides a competitive advantage to the global firms

    A Data Transformation System for Biological Data Sources

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    Scientific data of importance to biologists in the Human Genome Project resides not only in conventional databases, but in structured files maintained in a number of different formats (e.g. ASN.1 and ACE) as well a.s sequence analysis packages (e.g. BLAST and FASTA). These formats and packages contain a number of data types not found in conventional databases, such as lists and variants, and may be deeply nested. We present in this paper techniques for querying and transforming such data, and illustrate their use in a prototype system developed in conjunction with the Human Genome Center for Chromosome 22. We also describe optimizations performed by the system, a crucial issue for bulk data

    Towards a management framework for data semantic conflicts : a financial applications perspective

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    Includes bibliographical references (p. 23-25).Raphael Yahalom and Stuart E. Madnick
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