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CHAPTER 2 THE ANATOMY OF A DATABASE SYSTEM
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The ESRI product suite of GIS applications contains a product called the Geodatabase (shorthand for geographic database), which supports the storage and management of geographic data elements. The Geodatabase is an object-relational database that supports spatial data. It is an example of a spatial database that is implemented as an ORDBS.
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Note There is no requirement that spatial database systems be implemented in ORDBSs or even OODBSs.
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ESRI has chosen to implement the Geodatabase as an ORDBS. More importantly, GIS data could be stored in an RDBS that has been extended to support spatial data. Behold! That is exactly what has happened with MySQL. MySQL AB has added a spatial data engine to their RDBS.
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Although it is true that ORDBSs are based on relational database platforms, they also provide some layer of data encapsulation and behavior. Most ORDBSs are specialized forms of RDBSs. Those database vendors who provide ORDBSs often build extensions to the statement-response interfaces by modifying the SQL to contain object descriptors and spatial query mechanisms. These systems are generally built for a particular application and are, like OODBSs, limited in their general use.
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Relational Database Systems
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An RDBS is a data storage and retrieval service based on the Relational Model of Data as proposed by E. F. Codd in 1970. These systems are the standard storage mechanism for structured data. A great deal of research is devoted to refining the essential model proposed by Codd, as discussed by C. J. Date in The Database Relational Model: A Retrospective Review and Analysis.3 This evolution of theory and practice is best documented in The Third Manifesto.4 The relational model is an intuitive concept of a storage repository (database) that can be easily queried by using a mechanism called a query language to retrieve, update, and insert data. The relational model has been implemented by many vendors because it has a sound systematic theory, a firm mathematical foundation, and a simple structure. The most commonly used query mechanism is Structured Query Language (SQL), which resembles natural language. Although SQL is not included in the relational model, SQL provides an integral part of the practical application of the relational model in RDBSs. The data is represented as related pieces of information (attributes) about a certain entity. The set of values for the attribute is formed as a tuple (sometimes called a record). Tuples are then stored in tables containing tuples that have the same set of attributes. Tables can then be related to other tables through constraints on domains, keys, attributes, and tuples.
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3. C. J. Date, The Database Relational Model: A Retrospective Review and Analysis (Reading, MA: Addison-Wesley, 2001). 4. C. J. Date and H. Darwen, Foundation for Future Database Systems: The Third Manifesto (Reading, MA: Addison-Wesley, 2000).
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CHAPTER 2 THE ANATOMY OF A DATABASE SYSTEM
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Many mistakenly consider a record as a colloquialism for tuple. One important distinction is that a tuple is a set of ordered elements whereas a record is a collection of related items without a sense of order. However, the order of the columns is important in the concept of a record. Interestingly, in SQL a result from a query can be a record whereas in relational theory each result is a tuple. Many texts use these terms interchangeably, creating a source of confusion for many.
The query language of choice for most implementations is Structured Query Language (SQL). SQL was proposed as a standard in the 1980s and is currently an industry standard. Unfortunately, many seem to believe SQL is based on relational theory and therefore is a sound theoretical concept. This misconception is perhaps fueled by a phenomenon brought on by industry. Almost all RDBSs implement some form of SQL. This popularity has mistakenly overlooked the many sins of SQL, including the following: SQL does not support domains as described by the relational model. In SQL, tables can have duplicate rows. Results (tables) can contain unnamed columns and duplicate columns. The implementation of nulls (missing values) by host database systems has been shown to be inconsistent and incomplete. Thus, many incorrectly associate the mishandling of nulls with SQL when in fact SQL merely returns the results as presented by the database system.5 The technologies used in RDBSs are many and varied. Some systems are designed to optimize some portion of the relational model or some application of the model to data. Applications of RDBSs range from simple data storage and retrieval to complex application suites with complex data, processes, and workflows. This could be as simple as a database that stores your compact disc or DVD collection, or a database designed to manage a hotel reservation system, or even a complex distributed system designed to manage information on the Web. As I mentioned in 1, many web applications (especially those that make up Web 2.0; see the accompanying sidebar) implement the LAMP stack whereby MySQL becomes the database for storage of the data hosted.
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