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Most DBMS vendors supply many secondary programs around their DBMS software. I refer to all these programs with the generic term tools. These tools allow users to perform tasks such as the following: Generate reports Build standard data-entry and data-retrieval screens Process database data in text documents or in spreadsheets Administer the database
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Database applications are application programs that use an underlying database to store their data. Examples of such database applications are screen- and menu-driven data-entry programs, spreadsheets, report generators, and so on. Database applications are often developed using development tools from the DBMS vendor. In fact, most of these development tools can be considered to be database applications themselves, because they typically use the database not only to store regular data, but also to store their application specifications. For example, consider tools such as Oracle JDeveloper and Oracle Application Express. With these examples we are entering the relational world, which is introduced in the next section.
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DBMS Terms Review
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In this section, the following terms were introduced: Database Database management system (DBMS) Kernel
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RELATIONAL DATABASE SYSTEMS AND ORACLE
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1.4 Relational Database Management Systems
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The theoretical foundation for a relational database management system (RDBMS) was laid out in 1970 by Ted Codd in his famous article A Relational Model of Data for Large Shared Data Banks (Codd, 1970). He derived his revolutionary ideas from classical components of mathematics: set theory, relational calculus, and relational algebra. About ten years after Ted Codd published his article, around 1980, the first RDBMS systems (Relational DBMS systems) aiming to translate Ted Codd s ideas into real products became commercially available. Among the first pioneering RDBMS vendors were Oracle and Ingres, followed a few years later by IBM with SQL/DS and DB2. We won t go into great detail about this formal foundation for relational databases, but we do need to review the basics in order to explain the term relational. The essence of Ted Codd s ideas was two main requirements: Clearly distinguish the logical task (the what) from the physical task (the how) both while designing, developing, and using databases. Make sure that an RDBMS implementation fully takes care of the physical task, so the system users need to worry only about executing the logical task.
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These ideas, regardless of how evident they seem to be nowadays, were quite revolutionary in the early 1970s. Most DBMS implementations in those days did not separate the logical and physical tasks at all; did not have a solid theoretical foundation of any kind; and offered their users many surprises, ad hoc solutions, and exceptions. Ted Codd s article started a revolution and radically changed the way people think about databases. What makes a DBMS a relational DBMS In other words: how can we determine how relational a DBMS is To answer this question, we must visit the theoretical foundation of the relational model. The following two sections discuss two important aspects of the relational model: relational data structures and relational operators. After these two sections, we will address another question: how relational is my DBMS
1.5 Relational Data Structures
This section introduces the most important relational data structures and concepts: Tables, columns, and rows The information principle Datatypes Keys Missing information and null values
RELATIONAL DATABASE SYSTEMS AND ORACLE
Tables, Columns, and Rows
The central concept in relational data structures is the table or relation (from which the relational model derives its name). A table is defined as a set of rows, or tuples. The rows of a table share the same set of attributes; a row consists of a set of (attribute name; attribute value) pairs. All data in a relational database is represented as column values within table rows. In summary, the basic relational data structures are as follows: A database, which is a set of tables A table, which is a set of rows A row, which is a set of column values
The definition of a row is a little sloppy. A row is not just a set of column values. A more precise definition would be as follows: A row is a set of ordered pairs, where each ordered pair consists of an attribute name with an associated attribute value. For example, the following is a formal and precise way to represent a row from the DEPARTMENTS table: {(deptno;40),(dname;HR),(location;Boston),(mgr;7839)} This row represents department 40: the HR department in Boston, managed by employee 7839. It would become irritating to represent rows like this; therefore, this book will use less formal notations as much as possible. After all, the concept of tables, rows, and columns is rather intuitive. In most cases, there is a rather straightforward one-to-one mapping between the entities of the data model and the tables in a relational database. The rows represent the occurrences of the corresponding entity, and the column headings of the table correspond with the attributes of that entity. See Figure 1-1 for an illustration of the DEPARTMENTS table.
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