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)
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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