Transition Of Traditional Relational Database Capstone Project

Length: 26 pages Sources: 10 Subject: Education - Computers Type: Capstone Project Paper: #28885319 Related Topics: Object Oriented, John Wesley, Technical Writing, Paradigm Shift
Excerpt from Capstone Project :

They in short link and map ideas that already exist, creating real time answers to questions as they are applied to new and archived knowledge or action plans.

According to IDC reports, most data warehouses will be stored in a columnar fashion and not in rows, reporting and data collection problems will be solved with databases that have no formal schema at all, horizontal scalability through clustering will be achieved by large-scale database servers; and most OLTP databases will either reside entirely in memory or be augmented by an in-memory database. These new systems will encourage companies to forget disk-based partitioning schemes, buffer management, indexing strategies and embrace a world of large-memory models, many processors with many cores, clustered servers and highly compressed column wise storage. (Prakash, 2010)

The formats mentioned her by Prakash (2010) are fundamentally responsive to a new form of data storage and formatting, where objects are saved as objects, rather than as object types or keyword searched data bits. In Kopteff's (2008) technical work the author demonstrates a direct comparison between an object relational database (Hibernates) to an object oriented database program (Versant), on several levels. In this work Kopteff (2010), concludes that the object database program was in fact easier to use and provided more rapid access to the user, due almost entirely to the fact that the object-based format did not have imbedded issues of mismatching, as well as secondary issues of development that allowed the developer to avoid the concerns of object relational mapping conversions.

From the usage section we can conclude, that using Versants interfaces is at least equally easy than using Hibernates interfaces and in most cases easier, since it lacks the object-relational mismatch configuration. Using an object database lets the developer focus on actual design problems and not on the problems of the ORM tool or the conversion of objects to relational form. When considering the results of the performance comparison, Versant was faster in most cases, hence it is more efficient to use. When looking at the results as a whole we can conclude that Versant is more useful for developing applications, since users can use Versant to develop applications more efficiently and with less workload, than with Hibernate. This also results savings in costs, which could be one of the key factors for the usage of object database to spread. (Kopteff, 2008, p. 11)

The overall intentions of the work were to present the viability and applicability of replacing object relational mapping programs, which take objects and codify them rather than simply organizing and storing them as objects in their true form, with object database systems. Clearly in the application of these two systems in a controlled setting the researcher makes a case for stepping up next-generation development, rather than simply attempting to place older templates on new knowledge-based demands.

Discussing the issue of Knowledge Management can be secondary to the highly technical discussion of how such information is stored, and in what form as relational database technology can answer many of the existing needs for knowledge management. Yet, clearly the object database format, with its many pros can be seen as a plausible answer to knowledge management. As Segev points out in a 2010 article on application of Knowledge Management to a usable database system most knowledge management databases are geared toward larger organizations, and the ease of development is largely ignored, as the need to develop outweighs potential cost of doing so. The point Segev makes is that small and medium sized organizations are now seeking knowledge management systems that offer ease of use and rapid access to applicable data. This transition implies that the databases that provide access to archival, new and transformative data must streamline and become more accessible for both internal and web based application. (2010) the easy leap is that they should do so using object oriented database technologies, as they remove a great deal of obstacles, and will prove to be time-saving devices that can be programmed to meet specific needs of the users. Given that small business make up the majority of businesses in the U.S. The need for applicable database technology for knowledge OBD knowledge management tools is obvious. According to the U.S. Census Bureau in 2004 there were just short of 5 million (4,980,165) businesses in the U.S. that employ between 1 and 99 employees. (U.S. Census Bureau, 2010) These businesses form the backbone of the American economy and if successful continually seek to improve technology,...


OBD and knowledge management technology may seem an illogical choice for some, but even the smallest business needs to stay competitive as few businesses successfully endure based on sheer luck and the skill of a single person on plan. These businesses, to stay competitive will be seeking database technology and will likely seek skilled it consultants if not employees to help them better organize and grow their business.

Rationale and Systems Analysis

The focus of database technology over the last 30 years has been placed almost exclusively in the development of traditional database technology. Ultimately, though exceedingly useful this technology does not consider or handle items as objects, offering only very limited utilization of multimedia all in one next-generation technology nor does it solve the many problems associated with mismatching errors, or most importantly offer search free time savings. Knowledge database technology, which is in a sense a form of artificial intelligence offers the ability of users, be they machines or humans the opportunity to solve knowledge-based questions or concerns using historical data and logical rapid reasoning. These two monumental but distinct forms of database technology are the next generation of database systems and offer users countless productivity improvements. This being said the time frame for such developments has been set aside, in large part due to the increases in hardware and software technology that can manage much larger database forms either in house or in secondary server locations. The need to create and offer systems that manage much larger compilations of data and at a much more rapid rate is likely the source of setting such technologies aside. Though there are forms of the technology that can be added to existing databases these are but temporary fixes and serve only to delay a monumental need that will arise in the future.

Though it is clear that information technology and database technology have led many to believe that knowledge and object-based database technology has significant merit, and will likely be the wave of the future current technology alone cannot create such as system. The technology to create such systems lies not only in the conception of the possibilities, but in the actual development of standalone database systems that are knowledge and object based. We now know that a chemist in Iowa can rapidly access all the information he or she needs to determine the current state of research (usually within a company or academic database) or he or she can contact other chemists anywhere in the world yet, the systems of contact and knowledge gathering are still laborious. The result is then individuals still feeling as if they are working in a vacuum or that they cannot gain such knowledge without taking time away from the main focus of research their research. This analogy is one of many that can be posed as proof that this technology must expand to next-generation knowledge and object database standards. Knowledge management databases in congruence with object database systems would, to some degree allow real time interaction between individuals, organizations, and the data they need to make decisions and streamline information. Rationale for this study is to support users, both large and small to expand database technology in a system that will allow for the mass storage and access capabilities for knowledge and object databases rather than continued reliance on traditional relational databases. "The widespread popularity of object-relational mapping (ORM) tools still raises the question of using an object database instead of a redundant data mapping tool and persisting data in its natural form -- as objects." (Kopteff, 2008, p. 1)

A systems analysis is clearly due in this area, as current database technology has developed in a very random pattern, to meet the immediate needs of programmers, users and organizations as well as to fit within the parameters of current technologies. These current technologies according to most now support the ability of databases to be object-based rather than the stop gap solution of object relational or simply relational in format. (Kopteff, 2008) Yet, even those same users have clearly come to the end of their ability to use database system as they are. This is in part due to the expansion of knowledge itself, and particularly archived knowledge and due to the fact that those same users can see the possibilities of object based and knowledge-based databases but have yet to see them take hold. (McDermott, 2000, pp. 21-36) the systems analysis that was conducted to…

Sources Used in Documents:


Booch, G (1991).: Object-oriented Design with Applications. Benjamin Cummings, Redwood

Brodie, M., J. Mylopoulos and J. Schmidt,(1985). On Conceptual Modeling. Springer-Verlag.

Codd, E.F., (1970). A Relational Model for Large Shared Data Bank, CACM.

Date, C.J., (1985). An Introduction to Database System, Addison Wesley.
And Floobs Ltd. Retrieved June 1, 2010 from: (2010) Retrieved June 1, 2010 from:
Prakash, N. (2010) Next-generation database technologies. Express Computer Retrieved June 1, 2010 from:
Segev, E. (March, 2010) Mapping Knowledge Into a Database Model. Journal of Knowledge Management Practice, 11( 1) Retrieved June 1, 2010 from:
from the U.S. Census Bureau. Retrieved June 1, 2010 from:
Versant Website (2010) Versant Academic Program. Retrieved June 1, 2010 from:

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