IBM Products
While Oracle and Ingres raced to become commercial products, IBM’s System/R project had also turned into an effort to build a commercial product, named SQL/Data System (SQL/DS). IBM announced SQL/DS in 1981 and began shipping the product in 1982. In 1983, IBM announced a version of SQL/DS for VM/CMS, an operating system that was frequently used on IBM mainframes in corporate information center applications.

In 1983, IBM also introduced Database 2 (DB2), another relational DBMS for its mainframe systems. DB2 operated under IBM’s MVS operating system, the workhorse operating system used in large mainframe data centers. The first release of DB2 began shipping in 1985, and IBM officials hailed it as a strategic piece of IBM software technology. DB2 has since become IBM’s flagship relational DBMS, and with IBM’s weight behind it, DB2’s SQL became the de facto standard database language. DB2 technology has now migrated across all IBM product lines, from personal computers to network servers to mainframes. In 1997, IBM took the DB2 cross-platform strategy even further, by announcing DB2 versions for servers from IBM hardware rivals Sun Microsystems and Hewlett-Packard. DB2 on mainframes remains the centerpiece of IBM’s database strategy, however, and is a vital force in enterprise computing.



Commercial Acceptance
During the first half of the 1980s, the relational database vendors struggled for commercial acceptance of their products. The relational products had several disadvantages compared with the traditional database architectures. The performance of relational databases was seriously inferior to that of traditional databases. Except for the IBM products, the relational databases came from small upstart vendors. And, except for the IBM products, the relational databases tended to run on minicomputers rather than on IBM mainframes.

The relational products did have one major advantage, however. Their relational query languages (SQL, QUEL, and others) allowed users to pose ad hoc queries to the database— and get immediate answers—without writing programs. As a result, relational databases began slowly turning up in information center applications as decision-support tools. By May 1985, Oracle proudly claimed to have over 1000 installations. Ingres was installed in a comparable number of sites. DB2 and SQL/DS were also being slowly accepted and counted their combined installations at slightly over 1000 sites.

During the last half of the 1980s, SQL and relational databases were rapidly accepted as the database technology of the future. The performance of the relational database products improved dramatically. Ingres and Oracle, in particular, leapfrogged, with each new version claiming superiority over the competitor and two or three times the performance of the previous release. Improvements in the processing power of the underlying computer hardware also helped to boost performance.

Market forces also boosted the popularity of SQL in the late 1980s. IBM stepped up its evangelism of SQL, positioning DB2 as the data management solution for the 1990s.
Publication of the first ANSI/ISO standard for SQL (SQL1) in 1986 gave SQL official status as a standard. SQL also emerged as a standard on UNIX-based computer systems, whose popularity accelerated in the 1980s. As personal computers became more powerful and were linked in local area networks (LANs), they needed more sophisticated database management. PC database vendors embraced SQL as the solution to these needs, and minicomputer database vendors moved down market to compete in the emerging PC local area network market.

Through the early 1990s, steadily improving SQL implementations and dramatic improvements in processor speeds made SQL a practical solution for transaction processing applications. SQL became a key part of the client/server architecture that used PCs, local area networks, and network servers to build much lower-cost information processing systems. When the Internet and the dot-com boom burst upon the IT landscape, SQL found a new role as the database language for Internet applications and e-commerce.

SQL’s supremacy in the database world has not gone unchallenged. Object-oriented programming emerged in the 1990s as the method of choice for applications development, especially for personal computers and their graphical user interfaces. The object model, with its objects, classes, methods, and inheritance, did not fit well with the relational model of tables, rows, and columns of data. Early “object database” products included Servio Logic’s Gemstone, Graphael’s Gbase, and Ontologic’s Vbase. A new generation of venture capital–backed object database companies sprang up in the early to mid-1990s, hoping to make relational databases and their vendors obsolete, just as SQL had done to the earlier, nonrelational vendors. These products included Itasca Systems’ ITASCA, Fujitsu’s Jasmine, Matisse Software’s Matisse, Objectivity’s Objectivity/DB, Ontos, Inc.’s (renamed from Ontologic) ONTOS, O2 Technology’s O2, along with perhaps a half dozen others. However, SQL and the relational model more than withstood the challenge. A few of these products remain in the market today, but most have been acquired or simply faded away. For example, O2 Technology merged with several companies, was acquired by Informix, and Informix was later acquired by IBM. Total annual revenues for object-oriented databases are measured in the low millions of dollars, while SQL and relational database systems, tools, and services produce tens of billions of dollars of sales per year.

As SQL grew to address an ever-wider variety of data management tasks, the one sizefits- all approach of the earlier SQL products showed serious strain. Specialized database systems sprang up to support different market needs. One of the fastest-growing segments was data warehousing, where databases were used to search through huge amounts of data to discover underlying trends and patterns. A second major trend was the incorporation of new data types (such as multimedia data) and object-oriented principles into SQL. A third important segment was mobile databases for portable personal computers that could operate when sometimes connected to, and sometimes disconnected from, a centralized database system. Another important application segment was embedded databases for use within intelligent devices such as network equipment. In-memory databases emerged as another segment, designed for very high levels of performance, and stream-oriented databases focused on managing data as it flowed over a network.

Despite the emergence of subsegments of the database market, SQL has remained a common denominator across them all. Forty years after it first emerged, SQL has broadened tremendously, and SQL’s dominance as the database standard remains very strong. New challenges continue to emerge—the need to incorporate XML and its hierarchical data model and the need to support massive quantities of data to support data management on the scale of the Internet are two of the most recent. But the history of the past 40 years indicates that SQL and the relational model have a powerful ability to embrace and adapt to new data management needs.

Source of Information : MCGraw Hill - SQL the Complete Reference 3rd Edition (10-2009)

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The history of the SQL is intimately intertwined with the development of relational databases. The relational concept was originally developed by Edgar Frank “Ted” Codd, an IBM researcher. In June 1970, Codd published an article entitled “A Relational Model of Data for Large Shared Data Banks,” which outlined a mathematical theory of how data could be stored and manipulated using a tabular structure. Relational databases and SQL trace their origins to this article, which appeared in the Communications of the Association for Computing Machinery.


The Early Years
Codd’s article triggered a flurry of relational database research, including a major research project within IBM. The goal of the project, called System/R, was to prove the workability of the relational concept and to provide some experience in actually implementing a relational DBMS. Work on System/R began in the mid-1970s at IBM’s Santa Teresa laboratories in San Jose, California.

In 1974 and 1975, the first phase of the System/R project produced a minimal prototype of a relational DBMS. In addition to the DBMS itself, the System/R project included work on database query languages. One of these languages was called SEQUEL, an acronym for Structured English Query Language. In 1976 and 1977, the System/R research prototype was rewritten from scratch, and the new implementation was distributed to selected IBM customers for evaluation in 1978 and 1979. These early customer sites provided some actual user experience with System/R and its database language, which, for legal reasons, had been renamed SQL, or Structured Query Language. In 1979, the System/R research project came to an end, with IBM concluding that relational databases were not only feasible, but also could be the basis for a useful commercial product.


Early Relational Products
The System/R project and its SQL database language were well-chronicled in technical journals during the 1970s. Seminars on database technology featured debates on the merits of the new and heretical relational model. By 1976, it was apparent that IBM was becoming enthusiastic about relational database technology and that it was making a major commitment to SQL.

The publicity about System/R attracted the attention of a group of engineers in Menlo
Park, California, who decided that IBM’s research foreshadowed a commercial market for relational databases. In 1977 they formed a company, Relational Software, Inc., to build a relational DBMS based on SQL. Their product named Oracle, shipped in 1979 and became the first commercially available relational DBMS. Oracle beat IBM’s first product to market by a full two years, and Oracle ran on Digital’s VAX minicomputers, which were less expensive than IBM mainframes. The company aggressively sold the merits of the new relational style of database management and eventually renamed itself after its flagship product. Today, Oracle Corporation is the leading vendor of relational database management systems and a major vendor of enterprise applications based on the Oracle database, with annual sales of tens of billions of dollars.

Professors at the University of California’s Berkeley computer laboratories were also researching relational databases in the mid-1970s. Like the IBM research team, they built a prototype of a relational DBMS and called their system Ingres. The Ingres project included a query language named QUEL that, although more structured than SQL, was less Englishlike. Many database pioneers, key database developers, and founders of database startup companies trace their history back to the Berkeley Ingres project.

In 1980, several professors left Berkeley and founded Relational Technology, Inc., to build a commercial version of Ingres, which was announced in 1981. Ingres and Oracle quickly became bitter archrivals, but their rivalry helped to call attention to relational database technology in this early stage. Despite its technical superiority in many areas,
Ingres became a clear second-place player in the market, competing against the SQL-based capabilities (and the aggressive marketing and sales strategies) of Oracle. The original QUEL query language was effectively replaced by SQL in 1986, a testimony to the market power of the SQL standard. By the mid-1990s, the Ingres technology had been sold to Computer Associates, a leading mainframe software vendor. (Computer Associates sold its interest in Ingres to a private equity company in 2005.)

Source of Information : MCGraw Hill - SQL the Complete Reference 3rd Edition (10-2009)

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One of the major tasks of a computer system is to store and manage data. To handle this task, specialized computer programs known as database management systems began to appear in the late 1960s and early 1970s. A database management system, or DBMS, helped computer users to organize and structure their data and allowed the computer system to play a more active role in managing the data. Although database management systems were first developed on large mainframe systems, their popularity quickly spread to minicomputers, and then to computer workstations, personal computers, and specialized server computers.

Database management has also played a key role in the explosion of computer networking and the Internet. Early database systems ran on large, monolithic computer systems, where the data, the database management software, and the users or application programs accessing the database all operated on the same system. The 1980s and 1990s saw the explosion of a new client/server model for database access, in which a user or an application program running on a personal computer accesses a database on a separate computer system by using a network. In the late 1990s, the increasing popularity of the Internet and the World Wide Web impacted the architecture of data management again. Today, users require little more than a web browser to access and interact with databases, not only within their own organizations, but also around the world. These Internet-based architectures usually involve three or more computer systems—one that runs the web browser and interacts with the user, connected over the Internet to a second system that runs an application program or application server, which is in turn connected to a third system that runs the database management system.

Database management has become a very big business. Independent software companies and computer vendors ship billions of dollars’ worth of database management products every year. Virtually all enterprise-class computer applications that support the daily operation of large companies and other organizations use databases. These applications include some of the fastest-growing application categories, such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Supply Chain Management (SCM), Sales Force Automation (SFA), and financial applications. Specialized high-performance server computers optimized to run the most popular database software constitute a multibillion-dollar market, and low-cost servers used exclusively for data management add billions more. Databases provide the intelligence behind most transaction-oriented web sites, and they are used to capture and analyze user interactions with web sites. Database management thus touches every segment of the computer market.

Since the late 1980s, a specific type of DBMS, called a relational database management system (RDBMS), has become so popular that it is the standard database form. Relational databases organize data in a simple, tabular form and provide many advantages over earlier types of databases. SQL is specifically a relational database language used to work with relational databases.

Source of Information : MCGraw Hill - SQL the Complete Reference 3rd Edition (10-2009)

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The long-term trend in the database market is for databases to take on a progressively larger role in the overall data processing architecture. The pre-relational database systems basically handled only data storage and retrieval; application programs were responsible for navigating their way through the database, sorting and selecting data, and handling all processing of the data. With the advent of relational databases and SQL, the DBMS took on expanded responsibilities. Database searching and sorting were embodied in SQL language clauses and provided by the DBMS, along with the capability to summarize data. Explicit navigation through the database became unnecessary. Subsequent SQL enhancements such as primary key, foreign key (referential), and check constraints continued the trend, taking over data validation and data integrity functions that had remained the sole responsibility of application programs with earlier SQL implementations. At each step, having the DBMS take on more responsibility provided more centralized control and reduced the possibility of data corruption due to application programming errors.

In many information technology (IT) departments within large companies and organizations, this DBMS trend paralleled an organizational trend. The corporate database and the data it contains came to be viewed as a major corporate asset, and in many IT departments, a dedicated database administration (DBA) group emerged, with responsibility for maintaining the database, defining (and in some cases updating) the data it contained, and providing structured access to it. Other groups within the IT department, or elsewhere within the company, could develop application programs, reports, queries, or other logic that accessed the database. In most organizations, application programs, and the businesspeople using them, have had primary responsibility for updating the data within the database. However, the DBA group sometimes has had responsibility for updating reference (lookup) table data and for assisting with scripts and utilities to perform tasks such as the bulk loading of newly acquired data. But the security of the database, the permitted forms of access, and in general, everything within the realm of the database, became the province of the DBA.

Three important features of modern enterprise-scale relational databases—stored procedures, functions, and triggers—have been a part of this trend. Stored procedures can perform database-related application processing within the database itself. For example, a stored procedure might implement the application’s logic to accept a customer order or to transfer money from one bank account to another. Functions are stored SQL programs that return only a single value for each row of data. Unlike stored procedures, functions are invoked by referencing them in SQL statements in almost any clause where a column name can be used. This makes them ideal for performing calculations and data transformations on data to be displayed in query results or used in search conditions. Nearly all relational DBMS products come with a set of vendor-supplied functions for general use, and therefore functions added by local database users are often called user-defined functions. Triggers are used to automatically invoke the processing capability of a stored procedure based on conditions that arise within the database. For example, a trigger might automatically transfer funds from a savings account to a checking account if the checking account becomes overdrawn. The stored procedural SQL capabilities of the popular DBMS products have been significantly expanded in their major revisions during the late 1990s and 2000s.

Source of Information : MCGraw Hill - SQL the Complete Reference 3rd Edition

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The history of the SQL is intimately intertwined with the development of relational databases. The relational concept was originally developed by Edgar Frank “Ted” Codd, an IBM researcher. In June 1970, Codd published an article entitled “A Relational Model of Data for Large Shared Data Banks,” which outlined a mathematical theory of how data could be stored and manipulated using a tabular structure. Relational databases and SQL trace their origins to this article, which appeared in the Communications of the Association for Computing Machinery.


The Early Years
Codd’s article triggered a flurry of relational database research, including a major research project within IBM. The goal of the project, called System/R, was to prove the workability of the relational concept and to provide some experience in actually implementing a relational DBMS. Work on System/R began in the mid-1970s at IBM’s Santa Teresa laboratories in San Jose, California.

In 1974 and 1975, the first phase of the System/R project produced a minimal prototype of a relational DBMS. In addition to the DBMS itself, the System/R project included work on database query languages. One of these languages was called SEQUEL, an acronym for Structured English Query Language. In 1976 and 1977, the System/R research prototype was rewritten from scratch, and the new implementation was distributed to selected IBM customers for evaluation in 1978 and 1979. These early customer sites provided some actual user experience with System/R and its database language, which, for legal reasons, had been renamed SQL, or Structured Query Language. In 1979, the System/R research project came to an end, with IBM concluding that relational databases were not only feasible, but also could be the basis for a useful commercial product.


Early Relational Products
The System/R project and its SQL database language were well-chronicled in technical journals during the 1970s. Seminars on database technology featured debates on the merits of the new and heretical relational model. By 1976, it was apparent that IBM was becoming enthusiastic about relational database technology and that it was making a major commitment to SQL.

The publicity about System/R attracted the attention of a group of engineers in Menlo
Park, California, who decided that IBM’s research foreshadowed a commercial market for relational databases. In 1977 they formed a company, Relational Software, Inc., to build a relational DBMS based on SQL. Their product named Oracle, shipped in 1979 and became the first commercially available relational DBMS. Oracle beat IBM’s first product to market by a full two years, and Oracle ran on Digital’s VAX minicomputers, which were less expensive than IBM mainframes. The company aggressively sold the merits of the new relational style of database management and eventually renamed itself after its flagship product. Today, Oracle Corporation is the leading vendor of relational database management systems and a major vendor of enterprise applications based on the Oracle database, with annual sales of tens of billions of dollars.

Professors at the University of California’s Berkeley computer laboratories were also researching relational databases in the mid-1970s. Like the IBM research team, they built a prototype of a relational DBMS and called their system Ingres. The Ingres project included a query language named QUEL that, although more structured than SQL, was less Englishlike. Many database pioneers, key database developers, and founders of database startup companies trace their history back to the Berkeley Ingres project.

In 1980, several professors left Berkeley and founded Relational Technology, Inc., to build a commercial version of Ingres, which was announced in 1981. Ingres and Oracle quickly became bitter archrivals, but their rivalry helped to call attention to relational database technology in this early stage. Despite its technical superiority in many areas,
Ingres became a clear second-place player in the market, competing against the SQL-based capabilities (and the aggressive marketing and sales strategies) of Oracle. The original QUEL query language was effectively replaced by SQL in 1986, a testimony to the market power of the SQL standard. By the mid-1990s, the Ingres technology had been sold to Computer Associates, a leading mainframe software vendor. (Computer Associates sold its interest in Ingres to a private equity company in 2005.)

Source of Information : MCGraw Hill - SQL the Complete Reference 3rd Edition (10-2009)

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