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Zeitschriftenartikel zum Thema "Database management":
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Patcharaprutipakorn, Tuangthong, Direk Thongaraim und Nujcha Thatreenaranon. „Case Study: Database Management for Solid Waste Management Services“. International Journal of Future Computer and Communication 6, Nr. 3 (September 2017): 133–37. http://dx.doi.org/10.18178/ijfcc.2017.6.3.505.
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Petkov, Yulian Ivanov, und Alexandre Ivanov Chikalanov. „Innovative Proposals for Database Storage and Management“. Mathematics and Informatics LXV, Nr. 1 (28.02.2022): 45–52. http://dx.doi.org/10.53656/math2022-1-6-inn.
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At present, the problem of storing large data sets as a source of artificial intelligence acquires a geopolitical and strategic character. The most well-known and used type of databases so far are the relational (SQL databases) and nonrelational (NoSQL databases. The both approaches have some principle problems, which are described below. That publication presents two original approaches to overcoming some of these shortcomings. First one is Object-oriented model for storing data in a relational database. The second is Storage of non-relational data in a relational database according to previously freely created by the user models. Presented models were used as base for software development of more than ten middle and large size national and European scientific and industrial projects.
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Yasmeen, Mrs. „NOSQL Database Engines for Big Data Management“. International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (31.10.2018): 617–22. http://dx.doi.org/10.31142/ijtsrd18608.
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Short, Douglas D. „Microcomputer Database Management“. Urologic Clinics of North America 13, Nr. 1 (Februar 1986): 39–45. http://dx.doi.org/10.1016/s0094-0143(21)01529-9.
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Aparajitha., R. S. V., M. K. Kavitha, T. R. P. Monisha, T. S. B. Pavithra und Vinoth P. Raja. „Database Management Systems“. International Journal of Computer Applications 1, Nr. 8 (25.02.2010): 73–76. http://dx.doi.org/10.5120/179-310.
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Mandapuram, Mounika, und Md Faruk Hosen. „The Object-Oriented Database Management System versus the Relational Database Management System: A Comparison“. Global Disclosure of Economics and Business 7, Nr. 2 (31.12.2018): 89–96. http://dx.doi.org/10.18034/gdeb.v7i2.657.
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Both object-oriented and relational database management systems are referred to as DBMS. The web-scale is expanding at an incredible rate, and with it comes an increase in mobile applications, technologies, and social media platforms. The rapid growth of these technologies produces a variety of structured and unstructured data in various forms, each of which has various consequences for data security. Using RDBMS and OODBMS, this study's methodology outlines the development, installation, and management process of multiple and complicated data sets. This study gives a documented study comparing different kinds of data stored in databases by employing two types of database techniques: relational database method and object-oriented database technique. We use a different fingerprint database for the web and mobile devices. This database is also managed using different technologies, such as MySQL, and it accommodates data generated using distinct methods. In addition, this study explores the benefits and advantages of the various databases and determines the ideal database management system for organizations. According to the survey's findings, RDBMS stores data and the relationships between them in tables, but OODBMS stores data in objects, in a manner analogous to Object-Oriented Programming (OOP). According to the study's findings, the primary distinction between relational database management systems (RDBMS) and object-oriented database management systems (OODBMS) is that RDBMS is a Database Management System based on the relational model. In contrast, OODBMS is a Database Management System that facilitates creating and modeling data as objects.
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Almost all of the database products developed over the past few years are based on what is called the relational approach.The purpose of this thesis is to characterize a relational data base management system, we do this by studying the relational model in some depth.The relational model is not static, rather it has been evolving over time. We trace the evolution of the relational model. We will also consider the ramifications of the relational model for modern database systems. Department of Computer Science
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Beyers, Hector Quintus. „Database forensics : Investigating compromised database management systems“. Diss., University of Pretoria, 2013. http://hdl.handle.net/2263/41016.
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The use of databases has become an integral part of modern human life. Often the data
contained within databases has substantial value to enterprises and individuals. As
databases become a greater part of people’s daily lives, it becomes increasingly interlinked with human behaviour. Negative aspects of this behaviour might include criminal activity,
negligence and malicious intent. In these scenarios a forensic investigation is required to collect evidence to determine what happened on a crime scene and who is responsible for the crime. A large amount of the research that is available focuses on digital forensics,
database security and databases in general but little research exists on database forensics as such. It is difficult for a forensic investigator to conduct an investigation on a DBMS due to limited information on the subject and an absence of a standard approach to follow during a forensic investigation. Investigators therefore have to reference disparate sources of information on the topic of database forensics in order to compile a self-invented approach to investigating a database. A subsequent effect of this lack of research is that compromised DBMSs (DBMSs that have been attacked and so behave abnormally) are not considered or understood in the database forensics field. The concept of compromised DBMSs was illustrated in an article by Olivier who suggested that the ANSI/SPARC model can be used to assist in a forensic investigation on a compromised DBMS. Based on the ANSI/SPARC model, the DBMS was divided into four layers known as the data model, data dictionary, application schema and application data. The extensional nature of the first three layers can influence the application data layer and ultimately manipulate the results produced on the application data layer. Thus, it becomes problematic to conduct a forensic investigation on a DBMS if the integrity of the extensional layers is in question and hence the results on the application data layer cannot be trusted. In order to recover the integrity of a layer of the DBMS a clean layer (newly installed layer) could be used but clean layers are not easy or always possible to configure on a DBMS depending on the forensic scenario. Therefore a combination of clean and existing layers can be used to do a forensic investigation on a DBMS.
PROBLEM STATEMENT
The problem to be addressed is how to construct the appropriate combination of clean and existing layers for a forensic investigation on a compromised DBMS, and ensure the
integrity of the forensic results.
APPROACH
The study divides the relational DBMS into four abstract layers, illustrates how the layers
can be prepared to be either in a found or clean forensic state, and experimentally
combines the prepared layers of the DBMS according to the forensic scenario. The study
commences with background on the subjects of databases, digital forensics and database forensics respectively to give the reader an overview of the literature that already exists in these relevant fields. The study then discusses the four abstract layers of the DBMS and explains how the layers could influence one another. The clean and found environments are introduced due to the fact that the DBMS is different to technologies where digital forensics has already been researched. The study then discusses each of the extensional abstract layers individually, and how and why an abstract layer can be converted to a clean or found state. A discussion of each extensional layer is required to understand how unique each layer of the DBMS is and how these layers could be combined in a way that enables a forensic investigator to conduct a forensic investigation on a compromised DBMS. It is illustrated that each layer is unique and could be corrupted in various ways. Therefore,
each layer must be studied individually in a forensic context before all four layers are
considered collectively. A forensic study is conducted on each abstract layer of the DBMS
that has the potential to influence other layers to deliver incorrect results. Ultimately, the
DBMS will be used as a forensic tool to extract evidence from its own encrypted data and
data structures. Therefore, the last chapter shall illustrate how a forensic investigator can
prepare a trustworthy forensic environment where a forensic investigation could be
conducted on an entire PostgreSQL DBMS by constructing a combination of the
appropriate forensic states of the abstract layers.
RESULTS
The result of this study yields an empirically demonstrated approach on how to deal with a compromised DBMS during a forensic investigation by making use of a combination of
various states of abstract layers in the DBMS. Approaches are suggested on how to deal
with a forensic query on the data model, data dictionary and application schema layer of
the DBMS. A forensic process is suggested on how to prepare the DBMS to extract
evidence from the DBMS. Another function of this study is that it advises forensic
investigators to consider alternative possibilities on how the DBMS could be attacked.
These alternatives might not have been considered during investigations on DBMSs to
date. Our methods have been tested at hand of a practical example and have delivered
promising results. Dissertation (MEng)--University of Pretoria, 2013. gm2014 Electrical, Electronic and Computer Engineering unrestricted
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Zhang, Hao. „Querying databases a tale of two C# approaches /“. Click here for download, 2010. http://proquest.umi.com.ps2.villanova.edu/pqdweb?did=2019786971&sid=1&Fmt=2&clientId=3260&RQT=309&VName=PQD.
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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. Includes bibliographical references (leaves 62-65). Also available in electronic version. Access restricted to campus users.
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Fredstam, Marcus, und Gabriel Johansson. „Comparing database management systems with SQLAlchemy : A quantitative study on database management systems“. Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-155648.
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Knowing which database management system to use for a project is difficult to know in advance. Luckily, there are tools that can help the developer apply the same database design on multiple different database management systems without having to change the code. In this thesis, we investigate the strengths of SQLAlchemy, which is an SQL toolkit for Python. We compared SQLite, PostgreSQL and MySQL using SQLAlchemy as well as compared a pure MySQL implementation against the results from SQLAlchemy. We conclude that, for our database design, PostgreSQL was the best database management system and that for the average SQL-user, SQLAlchemy is an excellent substitution to writing regular SQL.
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Lo, Chi Lik Eric. „Test automation for database management systems and database applications /“. Zürich : ETH, 2007. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17271.
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Khayundi, Peter. „A comparison of open source object-oriented database products“. Thesis, University of Fort Hare, 2009. http://hdl.handle.net/10353/254.
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Object oriented databases have been gaining popularity over the years. Their ease of use and the advantages that they offer over relational databases have made them a popular choice amongst database administrators. Their use in previous years was restricted to business and administrative applications, but improvements in technology and the emergence of new, data-intensive applications has led to the increase in the use of object databases. This study investigates four Open Source object-oriented databases on their ability to carry out the standard database operations of storing, querying, updating and deleting database objects. Each of these databases will be timed in order to measure which is capable of performing a particular function faster than the other.
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Bhasker, Bharat. „Query processing in heterogeneous distributed database management systems“. Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/39437.
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The goal of this work is to present an advanced query processing algorithm formulated and developed in support of heterogeneous distributed database management systems. Heterogeneous distributed database management systems view the integrated data through an uniform global schema. The query processing algorithm described here produces an inexpensive strategy for a query expressed over the global schema. The research addresses the following aspects of query processing: (1) Formulation of a low level query language to express the fundamental heterogeneous database operations; (2) Translation of the query expressed over the global schema to an equivalent query expressed over a conceptual schema; (3) An estimation methodology to derive the intermediate result sizes of the database operations; (4) A query decomposition algorithm to generate an efficient sequence of the basic database operations to answer the query. This research addressed the first issue by developing an algebraic query language called cluster algebra. The cluster algebra consists of the following operations: (a) Selection, union, intersection and difference, which are extensions of their relational algebraic counterparts to heterogeneous databases; (b) Normal-join and normal-projection which replace their counterparts, join and projection, in the relational algebra; (c) Two new operators embed and unembed to restructure the database schema. The second issue of the query translation was addressed by development of an algorithm that translates a cluster algebra query expressed over the virtual views to an equivalent cluster algebra query expressed over the conceptual databases. A non-parametric estimation methodology to estimate the result size of a cluster algebra operation was developed to address the third issue described above. Finally, this research developed a query decomposition algorithm, applicable to the relational and non-relational databases, that decomposes a query by computing all profitable semi-join operations, followed by the determination of the best sequence of join operations per processing site. The join optimization is performed by formulating
a zero-one integer linear program that uses the non-parametric estimation technique
to compute the sizes of intermediate results. The query processing algorithm was
implemented in the context of DAVID, a heterogeneous distributed database
management system. Ph. D.
DiCostanzo, Carmine. Database management. Juneau, Alaska: Alaska Dept. of Fish and Game, Division of Commercial Fisheries, Computer Services Section, 1993.
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DiCostanzo, Carmine. Database management. Juneau, Alaska: Alaska Dept. of Fish and Game, Division of Commercial Fisheries, Computer Services Section, 1993.
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Wingerath, Wolfram, Norbert Ritter und Felix Gessert. „Database Management“. In Real-Time & Stream Data Management, 9–19. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10555-6_2.
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Genesereth, Michael, und Vinay K. Chaudhri. „Database Management“. In Introduction to Logic Programming, 125–28. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-031-01586-1_15.
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Kaufmann, Michael, und Andreas Meier. „Database Management“. In SQL and NoSQL Databases, 1–24. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27908-9_1.
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Blattberg, Robert C., Byung-Do Kim und Scott A. Neslin. „Churn Management“. In Database Marketing, 607–33. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-72579-6_24.
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Closa, Daniel, Alex Gardiner, Falk Giemsa und Jörg Machek. „Database and Database Management System“. In Patent Law for Computer Scientists, 75–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05078-7_5.
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Konferenzberichte zum Thema "Database management":
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Rabuzin, Kornelije, Sonja Ristić und Robert Kudelić. „GRAPH DATABASE MANAGEMENT SYSTEMS AND GRAPH THEORY“. In Fourth International Scientific Conference ITEMA Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/itema.2020.39.
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In recent years, graph databases have become far more important. They have been proven to be an excellent choice for storing and managing large amounts of interconnected data. Since graph databases (GDB) rely on a graph data model based on graph theory, this study examines whether currently available graph database management systems support the principles of graph theory, and, if so, to what extent. We also show how these systems differ in terms of implementation and languages, and we also discuss which graph database management systems are used today and why.
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Joy, Steven P., Todd A. King und Raymond J. Walker. „Automating database management for distributed database systems“. In The earth and space science information system (ESSIS). AIP, 1993. http://dx.doi.org/10.1063/1.44412.
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Halevy, Alon Y. „User-focused database management“. In Proceedingsc of the 13th international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1502650.1502654.
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Patchigolla, Venkata N. Ramarekha, John Springer und Kyle Lutes. „Embedded Database Management Performance“. In 2011 Eighth International Conference on Information Technology: New Generations (ITNG). IEEE, 2011. http://dx.doi.org/10.1109/itng.2011.171.
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Ghafoor, Arif. „Multimedia database management systems“. In Laser Beam Propagation in the Atmosphere, herausgegeben von Hugo Weichel. SPIE, 2017. http://dx.doi.org/10.1117/12.2284072.
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Xu, Wenhao, Jing Li, Yongwei Wu, Xiaomeng Huang und Guangwen Yang. „VDM: Virtual Database Management for Distributed Databases and File Systems“. In 2008 Seventh International Conference on Grid and Cooperative Computing (GCC). IEEE, 2008. http://dx.doi.org/10.1109/gcc.2008.42.
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Mok, Wai Yin. „A Logical Database Design Methodology for MongoDB NoSQL Databases“. In 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2021. http://dx.doi.org/10.1109/ieem50564.2021.9673004.
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Ghandeharizadeh, Shahram, und Jason Yap. „Cache augmented database management systems“. In the ACM SIGMOD Workshop. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2484702.2484709.
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Boral, Hanan. „Panel: Database system performance management“. In the 1986 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 1986. http://dx.doi.org/10.1145/16894.16869.
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Berichte der Organisationen zum Thema "Database management":
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Leishman, N. L. Management Information Database System. Office of Scientific and Technical Information (OSTI), Mai 1989. http://dx.doi.org/10.2172/6004600.
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Dabrowski, Christopher E., Elizabeth N. Fong und Deyuan Yang. Object database management systems. Gaithersburg, MD: National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.sp.500-179.
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Dabrowski, Christopher, und Elizabeth Fong. Database Management Systems in engineering. Gaithersburg, MD: National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4987.
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Fong, Elizabeth N., und Bruce K. Rosen. Guide to distributed database management. Gaithersburg, MD: National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nbs.sp.500-154.
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MERRILL, KYLE J. Construction of file database management. Office of Scientific and Technical Information (OSTI), März 2000. http://dx.doi.org/10.2172/752799.
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Gochanour, Jason Robert. Proposal Management and Sample Tracking Database. Office of Scientific and Technical Information (OSTI), Juni 2019. http://dx.doi.org/10.2172/1526922.
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Ralston, Lynda M., Andrew M. Bardos, William R. Beaudet und Lee M. Burberry. Database Management Using Optical Associative Memory. Fort Belvoir, VA: Defense Technical Information Center, Februar 1998. http://dx.doi.org/10.21236/ada342499.
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Wilson, D. Region and database management for HANDI 2000 business management system. Office of Scientific and Technical Information (OSTI), August 1998. http://dx.doi.org/10.2172/362442.
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Arora, Jasbir S. Database Design and Management in Engineering Optimization. Fort Belvoir, VA: Defense Technical Information Center, Februar 1988. http://dx.doi.org/10.21236/ada193325.
