TAILIEUCHUNG - Lecture Database design, application development and administration - Chapter 17: Client-server processing, parallel database processing, and distributed databases

In this chapter, you will learn howcomputer networks, remote computers, and remote data storage can improve reliability and performance for both kinds of processing. This chapter explains the ways that DBMSs utilize computer networks, remote computers, and remote data storage. Before understanding the details, you should understand the motivation for utilizing these resources. | Chapter 17 Client-Server Processing, Parallel Database Processing, and Distributed Databases Welcome to chapter 17. Client-Server Processing and Distributed Databases can improve reliability and performance for transaction and decision support processing. This chapter describes how database management systems utilize computer networks, remote computers and remote data storage to support client-server processing, parallel database processing, and distributed databases. Outline Overview Client-Server Database Architectures Parallel Database Architectures Architectures for Distributed Database Management Systems Transparency for Distributed Database Processing Distributed Database Processing After this chapter, you should able to: - List reasons for client-server processing, parallel database processing, and distributed data - Describe two-tier, three-tier, and multiple-tier client-server database architectures - Describe common architectures for parallel database processing - Describe differences between technology for tightly integrated and loosely integrated distributed databases - Compare the different kinds of distributed database transparency - Understand the nature of query processing and transaction processing for distributed databases Evolution of Distributed Processing and Distributed Data Need to share resources across a network Timesharing (1970s) Remote procedure calls (1980s) Client-server computing (1990s) The technologies available for distributed processing and data have evolved from previous technologies. Even in the early days of computing, there was wide-spread recognition of the need to share resources across a network. Timesharing was a popular way to share resources in the 1970s. The advent of personal computers and local area networks spurred changes in distributed processing in the 1980s. Local area networks support high-speed data transfer while personal computers support rich graphical interfaces. Thus, larger amounts of data can be .

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