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I The ideal distributed database is one in which the user doesn t know and doesn t care that the data is distributed; to the user, all of the relevant data appears as if it were on the local system. I Because this ideal distributed DBMS is very difficult to provide and involves too many performance trade-offs, commercial DBMS products are providing distributed database capability in phases. I Remote database access can be useful in situations where the remote access is a small part of total database activity; in this case, it s more practical to leave the data in the remote location and incur the network overhead for each database access.
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I Database replication is very useful in situations where there is relatively heavy access to data in multiple locations; it brings the data closer to the point of access, but at the cost of network overhead for replica synchronization and data that is not 100 percent up to date. I The particular trade-offs of remote data access and replication strategies have implications beyond technology decisions; they should reflect underlying trade-offs in business priorities as well. I Enterprisewide distributed applications, Internet-based applications, data warehousing, and other trends are increasing the complexity of the distributed data management environment. The N-tier architectures they use will require smart data caching and replication strategies to deliver adequate performance.
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he only serious challenge to the dominance of SQL and relational database management over the last few years has come from the emergence of an equally significant trend the growing popularity of object-oriented technologies. Object-oriented programming languages (such as C++ and Java), object-oriented development tools, and object-oriented networking (including object request brokers, and more recently, Web Services) have emerged as foundation technologies for modern software development. Object technologies gained much of their initial popularity for building personal computer applications with graphical user interfaces. But their impact has grown, and they are being used today to build (and more importantly, to link together) enterprisewide network-based applications for large corporations. In the early 1990s, a group of venture-backed object-oriented database companies was formed with the goal of applying object-oriented principles to database management. These companies believed that their object-oriented databases would supplant the outdated relational databases as surely as the relational model had supplanted earlier data models. However, they met with limited marketplace success in the face of entrenched relational technologies and SQL. In response to the object challenge, many relational database vendors moved aggressively to graft object technologies onto their relational systems, creating hybrid object-relational models. This chapter describes the object database challenge to SQL and the resulting object-relational features provided by some major DBMS vendors.
Object-Oriented Databases
Considerable academic research on database technology over the past decade has been focused on new, post-relational data models. Just as the relational model provided clear-cut advantages over the earlier hierarchical and network models, the goal of this research was to develop new data models that would overcome some of the disadvantages of the relational model. Much of this research has focused on how to merge the principles of object-oriented programming and design with traditional database characteristics, such as persistent storage and transaction management. In addition to the academic research, in the early and mid-1990s, some large venture capital investments flowed into a group of startup software companies whose goal was to build a new generation of data management technologies. These companies typically started with the object data structures used by an object-oriented program to manage its in-memory data, and extended them for disk-based storage and multiuser access. Enthusiastic supporters of these object-oriented databases (OODBs) firmly believed that they would mount a serious challenge to the relational model and become the dominant database architecture by the end of the decade. That scenario proved far off the mark, but the object database vendors have had a significant impact on their relational rivals.
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