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Fredstam, Marcus, and 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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Kanani, Saleh. "A method to evaluate database management systems for Big Data : focus on spatial data." Thesis, Luleå tekniska universitet, Datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74172.
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Big data of type spatial is growing exponentially with the highest rate due to extensive growth in usage of sensors, IoT and mobile devices’ spatial data generation, therefore maintaining, processing and using such data efficiently, effectively with high performance has become one of the top priorities for Database management system providers, hence spatial database features and datatypes have become serious criteria in evaluating database management systems that are supposed to work as the back-end for spatial applications and services. With exponential growth of data and introducing of new types of data, “Big Data” has become strongly focused area that has gained the attention of different sectors e.g. academia, industries and governments to other organizations and studies. The rising trend in high resolution and large-scale geographical information systems have resulted in more companies providing location-based applications and services, therefore finding a proper database management system solution that can support spatial big data features, with multi-model big data support that is reliable and affordable has become a business need for many companies. Concerning the fact that choosing proper solution for any software project can be crucial due to the total cost and desired functionalities that any product could possibly bring into the solution. Migration is also a very complicated and costly procedure that many companies should avoid, which justifies the criticality of choosing the right solution based on the specific needs of any organization. Companies providing spatial applications and services are growing with the common concern of providing successful solutions and robust services. One of the most significant elements that ensures services’ and hence the providers’ reputation and positive depiction is services’ high availability. The possible future work for the thesis could be to develop the framework into a decision support solution for IT businesses with emphasize on spatial features. Another possibility for the future works would be to evaluate the framework by testing the evaluation framework on many other different DBMSs.
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Lehner, Wolfgang. "Energy-Efficient In-Memory Database Computing." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-115547.
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The efficient and flexible management of large datasets is one of the core requirements of modern business applications. Having access to consistent and up-to-date information is the foundation for operational, tactical, and strategic decision making. Within the last few years, the database community sparked a large number of extremely innovative research projects to push the envelope in the context of modern database system architectures. In this paper, we outline requirements and influencing factors to identify some of the hot research topics in database management systems. We argue that—even after 30 years of active database research—the time is right to rethink some of the core architectural principles and come up with novel approaches to meet the requirements of the next decades in data management. The sheer number of diverse and novel (e.g., scientific) application areas, the existence of modern hardware capabilities, and the need of large data centers to become more energy-efficient will be the drivers for database research in the years to come.
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Kernert, David. "Density-Aware Linear Algebra in a Column-Oriented In-Memory Database System." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-210043.
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Linear algebra operations appear in nearly every application in advanced analytics, machine learning, and of various science domains. Until today, many data analysts and scientists tend to use statistics software packages or hand-crafted solutions for their analysis. In the era of data deluge, however, the external statistics packages and custom analysis programs that often run on single-workstations are incapable to keep up with the vast increase in data volume and size. In particular, there is an increasing demand of scientists for large scale data manipulation, orchestration, and advanced data management capabilities. These are among the key features of a mature relational database management system (DBMS). With the rise of main memory database systems, it now has become feasible to also consider applications that built up on linear algebra.
This thesis presents a deep integration of linear algebra functionality into an in-memory column-oriented database system. In particular, this work shows that it has become feasible to execute linear algebra queries on large data sets directly in a DBMS-integrated engine (LAPEG), without the need of transferring data and being restricted by hard disc latencies. From various application examples that are cited in this work, we deduce a number of requirements that are relevant for a database system that includes linear algebra functionality. Beside the deep integration of matrices and numerical algorithms, these include optimization of expressions, transparent matrix handling, scalability and data-parallelism, and data manipulation capabilities. These requirements are addressed by our linear algebra engine. In particular, the core contributions of this thesis are: firstly, we show that the columnar storage layer of an in-memory DBMS yields an easy adoption of efficient sparse matrix data types and algorithms. Furthermore, we show that the execution of linear algebra expressions significantly benefits from different techniques that are inspired from database technology. In a novel way, we implemented several of these optimization strategies in LAPEG’s optimizer (SpMachO), which uses an advanced density estimation method (SpProdest) to predict the matrix density of intermediate results. Moreover, we present an adaptive matrix data type AT Matrix to obviate the need of scientists for selecting appropriate matrix representations. The tiled substructure of AT Matrix is exploited by our matrix multiplication to saturate the different sockets of a multicore main-memory platform, reaching up to a speed-up of 6x compared to alternative approaches. Finally, a major part of this thesis is devoted to the topic of data manipulation; where we propose a matrix manipulation API and present different mutable matrix types to enable fast insertions and deletes.
We finally conclude that our linear algebra engine is well-suited to process dynamic, large matrix workloads in an optimized way. In particular, the DBMS-integrated LAPEG is filling the linear algebra gap, and makes columnar in-memory DBMS attractive as efficient, scalable ad-hoc analysis platform for scientists.
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Tolvaišis, Andrius. "DBVS praplėtimo nauju funkcionalumu galimybių tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100826_110401-00307.
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Duomenų bazių valdymo sistema (DBVS) yra pagrindas beveik visų šiuolaikinių informacinių sistemų (IS). Iš esmės kiekvienas verslo, mokslo arba valdžios valdymo procesas remiasi duomenų baze. Interneto plėtra tik paspartino šią tendenciją – šiandien duomenų bazių operacijos yra kiekvieno duomenų pakeitimo didesniuose tinklalapiuose, paieškos arba apsipirkimo internete variklis [1].
Šiuo metu rinkoje yra didelis komercinių ir nemokamų (taip pat ir atviro kodo) duomenų bazių valdymo sistemų (DBVS) pasirinkimas, pavyzdžiui: Oracle, Microsoft SQL Server, IBM DB2, Microsoft Access, MySQL, PostgreSQL. Kiekviena jų turi savo privalumų ir trukumų. Tačiau informacinių sistemų projektavimo eiga, naudojant šias DBVS ir neatsižvelgiant į jų ypatumus, yra panaši: suprojektuojama duomenų bazė (sukuriamos lentelės, nustatomi jų tarpusavio ryšiai), rašomos užklausos, kuriamos (arba generuojamos) duomenų įvedimo/redagavimo formos bei kuriamos duomenų išrinkimo ataskaitos. Ši informacinių sistemų kūrimo tvarka yra nusistovėjusi per daugelį metų. Tačiau DB projektavimo procesas taptų lengvesnis, pakeitus IS projektavimo procesą taip, kad realizacijos metu iš pradžių būtų kuriamos formos, o tik po to iš sukurtų formų būtų generuojama duomenų bazė. Toks IS kūrimo procesas leistų iš dalies automatizuotų DB projektavimą. Be to, galutinai suderinus prototipus su užsakovu, užtektų tik sugeneruoti DB, t.y. nereikėtų iš naujo kurti formų, o sistema sugeneruotų DB bei automatiškai susietų formų laukus... [toliau žr. visą tekstą]<br>The Data Base Management System (DBMS) is the foundation of almost every modern business information system. Virtually every administrative process in business, science or government relies on a database. There are a lot of DBMS products in our days, such as Oracle, Microsoft SQL Server, IBM DB2, Microsoft Access, MySQL and PostgreSQL. Each of it has their advantages and disadvantages. But the database design process using these DBMS is the same – at the first stage we need to create a database (tables and relationships between them), then we need to create (or generate by using wizard) forms for data input/modification and reports for data selection. However, the database design process would become easier by changing database design process in such a way that at first we create forms and then database is generated from forms data and forms are automatically associated with database tables. The task of research is to extend chosen free open source DBMS by new functions which would enable to develop forms and DB using new methods – automated database generation from forms and automatic forms association with database tables. OpenOffice.org Base DBMS and Java programming language has been chosen for the task implementation. This thesis consists of analysis, design, user manual, experimental and conclusion parts.
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Wijesekera, Primal. "Scalable Database Management System (DBMS) architecture with Innesto." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43363.
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Database Management systems (DBMS) have been in the core of Information Systems
for decades and their importance is getting higher and higher with current
high growth in user demand and rising necessity to handle big data. With recent
emergence of new style of deployments in the cloud, decades old architectures
in DBMS have been greatly challenged due to their inability to scale beyond single
computing node and to handle big data. This new requirement has spawned
new directions along scaling data storage architectures. Most of the work surfaced
lacks the applicability across many domains as they were targeting only a specific
domain.
We present a novel scalable architecture which is implemented using a distributed
spatial partitioning tree (SPT). This new architecture replaces only the
storage layer of a conventional DBMS thus leaving its applicability across domains
intact and provides strict consistency and isolation. Indexing and locking are
two important components of a Relational Database Management System (DBMS)
which pose as potential bottleneck when scaling. Our new approach based on SPT
provides a novel scalable alternative for these components.
Our evaluations using the TPC-C workload show they are capable of scaling
beyond single computing node and support more concurrent users compared to a
single node conventional system. We believe our contributions to be an important
first step towards the goal of a scalable, cloud aware and full-featured DBMS as a
service.
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Atila, Yavuz Vural. "Design and implementation of a multimedia DBMS sound management integration /." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA245774.
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Thesis (M.S. in Engineering Science)--Naval Postgraduate School, December 1990.<br>Thesis Advisor(s): Lum, Vincent Y. Second Reader: Hsiao, David. "December 1990." Description based on title screen as viewed on ... DTIC Descriptor(s): Data bases, data management, sound, systems engineering, interfaces, alphanumeric data, integration, user needs, media, microcomputers, records, storage, sun, computers, local area networks, management, environments, theses DTIC Identifier(s): Data bases, systems engineering, sound, data management, MDBMS (multimedia database management system), theses, man computer interface, catalogs, data storage systems Author(s) subject terms: Multimedia Database Management System, Multimedia, DBMS, MDBMS, Sound Media Management, Sound Database Includes bibliographical references (p. 62-64).62 Also available in print.
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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.<br>Dissertation (MEng)--University of Pretoria, 2013.<br>gm2014<br>Electrical, Electronic and Computer Engineering<br>unrestricted
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Jäkel, Tobias. "Role-based Data Management." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-224416.
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Database systems build an integral component of today’s software systems and as such they are the central point for storing and sharing a software system’s data while ensuring global data consistency at the same time. Introducing the primitives of roles and their accompanied metatype distinction in modeling and programming languages, results in a novel paradigm of designing, extending, and programming modern software systems. In detail, roles as modeling concept enable a separation of concerns within an entity. Along with its rigid core, an entity may acquire various roles in different contexts during its lifetime and thus, adapts its behavior and structure dynamically during runtime.
Unfortunately, database systems, as important component and global consistency provider of such systems, do not keep pace with this trend. The absence of a metatype distinction, in terms of an entity’s separation of concerns, in the database system results in various problems for the software system in general, for the application developers, and finally for the database system itself. In case of relational database systems, these problems are concentrated under the term role-relational impedance mismatch. In particular, the whole software system is designed by using different semantics on various layers. In case of role-based software systems in combination with relational database systems this gap in semantics between applications and the database system increases dramatically. Consequently, the database system cannot directly represent the richer semantics of roles as well as the accompanied consistency constraints. These constraints have to be ensured by the applications and the database system loses its single point of truth characteristic in the software system. As the applications are in charge of guaranteeing global consistency, their development requires more effort in data management. Moreover, the software system’s data management is distributed over several layers, which results in an unstructured software system architecture.
To overcome the role-relational impedance mismatch and bring the database system back in its rightful position as single point of truth in a software system, this thesis introduces the novel and tripartite RSQL approach. It combines a novel database model that represents the metatype distinction as first class citizen in a database system, an adapted query language on the database model’s basis, and finally a proper result representation. Precisely, RSQL’s logical database model introduces Dynamic Data Types, to directly represent the separation of concerns within an entity type on the schema level. On the instance level, the database model defines the notion of a Dynamic Tuple that combines an entity with the notion of roles and thus, allows for dynamic structure adaptations during runtime without changing an entity’s overall type.
These definitions build the main data structures on which the database system operates. Moreover, formal operators connecting the query language statements with the database model data structures, complete the database model. The query language, as external database system interface, features an individual data definition, data manipulation, and data query language. Their statements directly represent the metatype distinction to address Dynamic Data Types and Dynamic Tuples, respectively. As a consequence of the novel data structures, the query processing of Dynamic Tuples is completely redesigned. As last piece for a complete database integration of a role-based notion and its accompanied metatype distinction, we specify the RSQL Result Net as result representation. It provides a novel result structure and features functionalities to navigate through query results. Finally, we evaluate all three RSQL components in comparison to a relational database system. This assessment clearly demonstrates the benefits of the roles concept’s full database integration.
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Behzadnia, Peyman. "Dynamic Energy-Aware Database Storage and Operations." Scholar Commons, 2018. http://scholarcommons.usf.edu/etd/7125.
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Energy consumption has become a first-class optimization goal in design and implementation of data-intensive computing systems. This is particularly true in the design of database management systems (DBMS), which is one of the most important servers in software stack of modern data centers. Data storage system is one of the essential components of database and has been under many research efforts aiming at reducing its energy consumption. In previous work, dynamic power management (DPM) techniques that make real-time decisions to transition the disks to low-power modes are normally used to save energy in storage systems. In this research, we tackle the limitations of DPM proposals in previous contributions and design a dynamic energy-aware disk storage system in database servers. We introduce a DPM optimization model integrated with model predictive control (MPC) strategy to minimize power consumption of the disk-based storage system while satisfying given performance requirements. It dynamically determines the state of disks and plans for inter-disk data fragment migration to achieve desirable balance between power consumption and query response time. Furthermore, via analyzing our optimization model to identify structural properties of optimal solutions, a fast-solution heuristic DPM algorithm is proposed that can be integrated in large-scale disk storage systems, where finding the most optimal solution might be long, to achieve near-optimal power saving solution within short periods of computational time. The proposed ideas are evaluated through running simulations using extensive set of synthetic workloads. The results show that our solution achieves up to 1.65 times more energy saving while providing up to 1.67 times shorter response time compared to the best existing algorithm in literature.
Stream join is a dynamic and expensive database operation that performs join operation in real-time fashion on continuous data streams. Stream joins, also known as window joins, impose high computational time and potentially higher energy consumption compared to other database operations, and thus we also tackle energy-efficiency of stream join processing in this research. Given that there is a strong linear correlation between energy-efficiency and performance of in-memory parallel join algorithms in database servers, we study parallelization of stream join algorithms on multicore processors to achieve energy efficiency and high performance. Equi-join is the most frequent type of join in query workloads and symmetric hash join (SHJ) algorithm is the most effective algorithm to evaluate equi-joins in data streams. To best of our knowledge, we are the first to propose a shared-memory parallel symmetric hash join algorithm on multi-core CPUs. Furthermore, we introduce a novel parallel hash-based stream join algorithm called chunk-based pairing hash join that aims at elevating data throughput and scalability. We also tackle parallel processing of multi-way stream joins where there are more than two input data streams involved in the join operation. To best of our knowledge, we are also the first to propose an in-memory parallel multi-way hash-based stream join on multicore processors. Experimental evaluation on our proposed parallel algorithms demonstrates high throughput, significant scalability, and low latency while reducing the energy consumption. Our parallel symmetric hash join and chunk-based pairing hash join achieve up to 11 times and 12.5 times more throughput, respectively, compared to that of state-of-the-art parallel stream join algorithm. Also, these two algorithms provide up to around 22 times and 24.5 times more throughput, respectively, compared to that of non-parallel (sequential) stream join computation where there is one processing thread.
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Lacordais, Sophie. "Analisi e confronto di Database Management System per la gestione di serie temporali IoT." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
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La tesi presenterà un confronto qualitativo e quantitativo tra Database Management System per la gestione di serie temporali IoT. Il confronto verrà effettuato tra RDBMS e TS-DBMS: in particolare verranno studiati rispettivamente PostgreSQL e InfluxDB.
Inizialmente viene introdotto il contesto in cui i dati delle serie temporali presentano una maggiore esigenza e il loro utilizzo. Presentato l'ambiente in cui si trovano questi dati, poi verrà definita l'architettura di base dei sistemi e la loro configurazione. A seguire, verranno illustreranno le tecniche e le query che andranno a definire lo studio dei test effettuati in entrambi i database. Assieme ad ogni test implementato, verranno mostrati i relativi risultati ottenuti calcolando la media del tempo di esecuzione. Raccolti i risultati dei test, sarà effettuato un confronto tra tali risultati sottoponendoli una breve introduzione del risultato in riferimento a tabelle e grafici ottenuti.
In conclusine, verranno fornite considerazioni in merito alle prestazioni dei database ed individuati eventuali sviluppi futuri.
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Liang, Xing, and Yongyu Lu. "EVALUATION OF DATABASE MANAGEMENT SYSTEMS." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-6255.
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Qualitative and quantitative analysis of different database management systems (DBMS) have been performed in order to identify and compare those which address requirements such as public domain licensing, free of charge, high product support, ADO .NET Entity Framework compatibility, good performance, referential integrity, among others. More than 20 existing database management systems have been selected as possible candidates. Qualitative analysis reduced that number to 4 candidates DBMSs (PostgreSQL, SQLite, Firebird and MySQL). Quantitative analysis has been used to test the performance of these 4 DBMSs while performing the most common structured query language (SQL) data manipulation statements (INSERT, UPDATE, DELETE and SELECT). Referential integrity and easy to install were also evaluated for these 4 DBMSs. As results, Firebird is the most suitable DBMS which best addressed all desired requirements.
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Alkahtani, Mufleh M. "Modeling relational database management systems." Virtual Press, 1993. http://liblink.bsu.edu/uhtbin/catkey/865955.
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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.<br>Department of Computer Science
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Peng, Rui. "Live video database management systems." Doctoral diss., University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4609.
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With the proliferation of inexpensive cameras and the availability of high-speed wired and wireless networks, networks of distributed cameras are becoming an enabling technology for a broad range of interdisciplinary applications in domains such as public safety and security, manufacturing, transportation, and healthcare. Today's live video processing systems on networks of distributed cameras, however, are designed for specific classes of applications. To provide a generic query processing platform for applications of distributed camera networks, we designed and implemented a new class of general purpose database management systems, the live video database management system (LVDBMS). We view networked video cameras as a special class of interconnected storage devices, and allow the user to formulate ad hoc queries over real-time live video feeds. In the first part of this dissertation, an Internet scale framework for sharing and dissemination of general sensor data is presented. This framework provides a platform for general sensor data to be published, searched, shared, and delivered across the Internet. The second part is the design and development of a Live Video Database Management System. LVDBMS allows users to easily focus on events of interest from a multitude of distributed video cameras by posing continuous queries on the live video streams. In the third part, a distributed in-memory database approach is proposed to enhance the LVDBMS with an important capability of tracking objects across cameras.<br>ID: 029049951; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2010.; Includes bibliographical references (p. 96-101).<br>Ph.D.<br>Doctorate<br>Department of Electrical Engineering and Computer Science<br>Engineering and Computer Science
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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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Kanchev, Kancho. "Employee Management System." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-1048.
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<p>This report includes a development presentation of an information system for managing the staff data within a small company or organization. The system as such as it has been developed is called Employee Management System. It consists of functionally related GUI (application program) and database.</p><p>The choice of the programming tools is individual and particular.</p>
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Goralwalla, Iqbal A. "Temporality in object database management systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ29042.pdf.
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Karatasios, Labros G. "Software engineering with database management systems." Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/27272.
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Scheuerl, S. "Modelling recovery in database systems." Thesis, University of St Andrews, 1998. http://hdl.handle.net/10023/13482.
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The execution of modern database applications requires the co-ordination of a number of components such as: the application itself, the DBMS, the operating system, the network and the platform. The interaction of these components makes understanding the overall behaviour of the application a complex task. As a result the effectiveness of optimisations are often difficult to predict. Three techniques commonly available to analyse system behaviour are empirical measurement, simulation-based analysis and analytical modelling. The ideal technique is one that provides accurate results at low cost. This thesis investigates the hypothesis that analytical modelling can be used to study the behaviour of DBMSs with sufficient accuracy. In particular the work focuses on a new model for costing recovery mechanisms called MaStA and determines if the model can be used effectively to guide the selection of mechanisms. To verify the effectiveness of the model a validation framework is developed. Database workloads are executed on the flexible Flask architecture on different platforms. Flask is designed to minimise the dependencies between DBMS components and is used in the framework to allow the same workloads to be executed on a various recovery mechanisms. Empirical analysis of executing the workloads is used to validate the assumptions about CPU, I/O and workload that underlie MaStA. Once validated, the utility of the model is illustrated by using it to select the mechanisms that provide optimum performance for given database applications. By showing that analytical modelling can be used in the selection of recovery mechanisms, the work presented makes a contribution towards a database architecture in which the implementation of all components may be selected to provide optimum performance.
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Battaglia, Bruno. "Studio e valutazione di database management system per la gestione di serie temporali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/17270/.
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La tesi è incentrata sulle time series e la loro gestione. Dopo aver esposto cosa fosse una serie temporale ed alcuni casi di utilizzo, la dissertazione prosegue elencando le famiglie di DBMS ed i criteri attraverso i quali valutarli. Successivamente si è descritto il modello che ogni DBMS implementava e, dopo aver dato un accenno di esso, si è passati alle tecniche usate per la gestione e l'analisi delle serie temporali. Ancora dopo, invece, si sono viste le tecniche di modellazione di un database in grado di gestire serie storiche e sono stati analizzati tutti i DBMS presi in esame attraverso i criteri sopracitati. Una comparazione, anche tramite forma tabellare, è stata accompagnata da una descrizione che potesse guidare il lettore ad una comprensione rapida delle differenze, dei punti di forza e delle debolezze di ogni TSDB. Infine sono state tratte le conclusioni che, in seguito al percorso svolto, sono sembrate più appropriate, sono stati individuati dei punti chiave su cui incentrare i lavori futuri e sono stati proposti altri spunti di lavoro ai quali non si è potuto lavorare per mancanza di ulteriore tempo e di disponibilità dei software completi di tutte le loro funzionalità.
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Дрозд, Віталій Михайлович, та Vitalii Drozd. "Методи та засоби проведення аудиту системи управління базами даних". Master's thesis, ТНТУ, 2021. http://elartu.tntu.edu.ua/handle/lib/36749.
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Методи та засоби проведення аудиту системи управління базами даних // Дипломна робота ОР «Магістр» // Дрозд Віталій Михайлович// Тернопільський національний технічний університет імені Івана Пулюя, факультет комп’ютерно-інформаційних систем і програмної інженерії, кафедра кібербезпеки, група СБм-61 // Тернопіль, 2021 // С. , рис. – 4, табл. – 0, кресл. – 0, додат. – 3 .<br>Дана магістерська кваліфікаційна робота присвячена дослідженню методів та засобів проведення аудиту систем управління баз даних. Проведено дослідження методів та засобів проведення аудиту системи управління баз даних.
Для проведення аудиту системи управління бази даних використано метод із використанням тригерів.
У першій главі проведено аналіз і класифікація підходів до аудиту баз даних.
У другій главі описані теоретичні відомості щодо проведення аудиту систем управління баз даних. Описано вбудовані засоби відстеження змін й оглянуто існуючі програми для аудиту.
У підрозділі «Охорона праці» розглянуто Закон про охорону праці й вимоги безпеки до робочих місць працівників з екранними пристроями. У підрозділі «Фактори що впливають на функціональний стан користувачів комп’ютерів» розглянуто різноманітні фактори які можуть впливати на функціональний стан користувачів комп’ютерів.<br>This master's thesis is devoted to the study of methods and tools for auditing database management systems. A study of methods and means of auditing the database management system.
The trigger method was used to audit the database management system.
The first chapter analyzes and classifies approaches to database auditing.
The second chapter describes the theoretical information on the audit of database management systems. Built-in change tracking tools are described and existing audit programs are reviewed.
In the subdivision "Labor protection" the Law on labor protection and safety requirements for workplaces of workers with screen devices is considered. The section "Factors affecting the functional status of computer users" discusses various factors that may affect the functional status of computer users.The first chapter presents existing approaches to text analysis.<br>ПЕРЕЛІК УМОВНИХ ПОЗНАЧЕНЬ, СИМВОЛІВ, ОДИНИЦЬ, СКОРОЧЕНЬ І ТЕРМІНІВ ... 7
ВСТУП ... 8
1 АНАЛІТИЧНА ЧАСТИНА ... 10
1.1 Класифікація підходів до аудиту баз даних ... 10
1.2 Аудит на рівні сервера ... 10
1.3 Аудит на рівні бази даних ... 11
1.4 Аудит за допомогою тригерів ... 11
1.5 Аудит за журналом транзакцій ... 13
2 ТЕОРЕТИЧНА ЧАСТИНА ... 14
2.1 Системи управління базами даних ...14
2.2 Структура журналу аудиту ... 18
2.3 Вбудовані засоби відстеження змін ... 20
2.3.1 Change Tracking ... 21
2.3.2 Change Data Capture ... 22
2.3.2 SQL Server Audit ... 23
2.3.3 SQL Server Profiler ... 23
2.4 Огляд існуючих програм для аудиту ... 24
3 ПРАКТИЧНА ЧАСТИНА ... 29
3.1 Розробка підсистеми аудиту ... 29
3.1.1 Логічне проектування ... 29
3.1.2 Інфологічне проектування ... 33
3.1.3 Фізичне проектування ... 38
3.2 Стрес-тестування ... 40
4 ОХОРОНА ПРАЦІ ТА ФАКТОРИ ЩО ВПЛИВАЮТЬ НА ФУКНЦІОНАЛЬНИЙ СТАН КОРИСТУВАЧІВ КОМП’ЮТЕРІВ ... 41
4.1 Охорона праці ... 41
4.2 Фактори що впливають на функціональний стан користувачів комп’ютерів ... 44
ВИСНОВКИ ... 48
БІБЛІОГРАФІЯ ... 50
ДОДАТКИ ... 52
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Ibrahim, Karim. "Management of Big Annotations in Relational Database Management Systems." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/272.
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Annotations play a key role in understanding and describing the data, and annotation management has become an integral component in most emerging applications such as scientific databases. Scientists need to exchange not only data but also their thoughts, comments and annotations on the data as well. Annotations represent comments, Lineage of data, description and much more. Therefore, several annotation management techniques have been proposed to efficiently and abstractly handle the annotations. However, with the increasing scale of collaboration and the extensive use of annotations among users and scientists, the number and size of the annotations may far exceed the size of the original data itself. However, current annotation management techniques don’t address large scale annotation management. In this work, we propose three chapters to that tackle the Big annotations from three different perspectives (1) User-Centric Annotation Propagation, (2) Proactive Annotation Management and (3) InsightNotes Summary-Based Querying. We capture users' preferences in profiles and personalizes the annotation propagation at query time by reporting the most relevant annotations (per tuple) for each user based on time plan. We provide three Time-Based plans, support static and dynamic profiles for each user. We support a proactive annotation management which suggests data tuples to be annotated in case new annotation has a reference to a data value and user doesn’t annotate the data precisely. Moreover, we provide an extension on the InsightNotes: Summary-Based Annotation Management in Relational Databases by adding query language that enable the user to query the annotation summaries and add predicates on the annotation summaries themselves. Our system is implemented inside PostgreSQL.
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Zou, Beibei 1974. "Data mining with relational database management systems." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82456.
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With the increasing demands of transforming raw data into information and knowledge, data mining becomes an important field to the discovery of useful information and hidden patterns in huge datasets. Both machine learning and database research have made major contributions to the field of data mining. However, there is still little effort made to improve the scalability of algorithms applied in data raining tasks. Scalability is crucial for data mining algorithms, since they have to handle large datasets quite often. In this thesis we take a step in this direction by extending a popular machine learning software, Weka3.4, to handle large datasets that can not fit into main memory by relying on relational database technology. Weka3.4-DB is implemented to store the data into and access the data from DB2 with a loose coupling approach in general. Additionally, a semi-tight coupling is applied to optimize the data manipulation methods by implementing core functionalities within the database. Based on the DB2 storage implementation, Weka3.4-DB achieves better scalability, but still provides a general interface for developers to implement new algorithms without the need of database or SQL knowledge.
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Dempster, Euan W. "Performance prediction for parallel database management systems." Thesis, Heriot-Watt University, 2004. http://hdl.handle.net/10399/341.
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Helmer, Sven. "Performance enhancements for advanced database management systems /." [S.l. : s.n.], 2000. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB8952361.
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Jeong, Byeong-Soo. "Indexing in parallel database systems." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/8189.
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Fu, Gregory Chung Yin. "Skyline queries in database systems /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?COMP%202003%20FU.
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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 51-52). Also available in electronic version. Access restricted to campus users.
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Mühlberger, Ralf Maximilian. "Data management for interoperable systems /." [St. Lucia, Qld.], 2001. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16277.pdf.
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Kanne, Carl-Christian. "Core technologies for native XML database management systems." [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10605041.
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Scott, Heidi. "User-level I/O for database management systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ59400.pdf.
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Tomov, Neven T. "Modelling parallel database management systems for performance prediction." Thesis, Heriot-Watt University, 1999. http://hdl.handle.net/10399/1263.
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Eaglestone, B. M. "Semantic-constraint modelling for small database management systems." Thesis, University of Huddersfield, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.354878.
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Sayli, Ayla. "Semantic query optimization in relational database management systems." Thesis, University of Essex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284608.
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CASTRO, LIESTER CRUZ. "TUNING OF DATABASE MANAGEMENT SYSTEMS IN VIRTUALIZED ENVIRONMENTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34071@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>Devido à enorme quantidade de dados nas aplicações atuais, observa-se o uso
crescente dos Sistemas Gerenciadores de Bancos de Dados Relacionais (SGBDR)
em ambientes virtualizados. Isto contribui para aumentar os requisitos das
operações de entrada e saída (E/S) das cargas de trabalho relacionadas. É
introduzida uma grande sobrecarga para aplicações intensivas em operações de E/S,
devida à virtualização dos dispositivos e ao escalonamento das máquinas virtuais.
Este trabalho tem por objetivo propor estratégias que permitam aumentar o
rendimento das operações de E/S gerenciadas pelos SGBDR em ambientes
virtualizados. Por meio da alocação de recursos computacionais, realizamos uma
sintonia fina nas ações do escalonador do ambiente virtualizado e também nos
parâmetros dos bancos de dados envolvidos. Para isso, foi desenvolvido um sistema
que trabalha de maneira coordenada com as diferentes camadas de virtualização.
Foram realizados experimentos que permitem avaliar e medir o impacto da
abordagem aqui proposta.<br>Due to the huge amount of data present in current applications there is a
growing use of Relational Database Management Systems (RDBMS) in virtualized
environments. This fact increases the workloads input/output (I/O) requirements
with respect to the corresponding workloads. This is due to resources virtualization
and virtual machines scheduling. Our work s goal is to propose strategies that
enable better performances for the I/O operations managed by the RDBMS.
Considering an intelligent assignment of computational resources, we have
executed fine tuning actions at the virtualized environment and on database
parameters. We consider a system that works coordinately with distinct
virtualization layers. We show some experimental results that evaluate and measure
the impact of our proposed approach.
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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.<br>Ph. D.
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Chan, Francis. "Knowledge management in Naval Sea Systems Command : a structure for performance driven knowledge management initiative." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FChan.pdf.
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Thesis (M.S. in Product Development)--Naval Postgraduate School, September 2002.<br>Thesis advisor(s): Mark E. Nissen, Donald H. Steinbrecher. Includes bibliographical references (p. 113-117). Also available online.
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Fischer, Ulrike. "Forecasting in Database Systems." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-133281.
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Time series forecasting is a fundamental prerequisite for decision-making processes and crucial in a number of domains such as production planning and energy load balancing. In the past, forecasting was often performed by statistical experts in dedicated software environments outside of current database systems. However, forecasts are increasingly required by non-expert users or have to be computed fully automatically without any human intervention. Furthermore, we can observe an ever increasing data volume and the need for accurate and timely forecasts over large multi-dimensional data sets. As most data subject to analysis is stored in database management systems, a rising trend addresses the integration of forecasting inside a DBMS. Yet, many existing approaches follow a black-box style and try to keep changes to the database system as minimal as possible. While such approaches are more general and easier to realize, they miss significant opportunities for improved performance and usability.
In this thesis, we introduce a novel approach that seamlessly integrates time series forecasting into a traditional database management system. In contrast to flash-back queries that allow a view on the data in the past, we have developed a Flash-Forward Database System (F2DB) that provides a view on the data in the future. It supports a new query type - a forecast query - that enables forecasting of time series data and is automatically and transparently processed by the core engine of an existing DBMS. We discuss necessary extensions to the parser, optimizer, and executor of a traditional DBMS. We furthermore introduce various optimization techniques for three different types of forecast queries: ad-hoc queries, recurring queries, and continuous queries. First, we ease the expensive model creation step of ad-hoc forecast queries by reducing the amount of processed data with traditional sampling techniques. Second, we decrease the runtime of recurring forecast queries by materializing models in a specialized index structure. However, a large number of time series as well as high model creation and maintenance costs require a careful selection of such models. Therefore, we propose a model configuration advisor that determines a set of forecast models for a given query workload and multi-dimensional data set. Finally, we extend forecast queries with continuous aspects allowing an application to register a query once at our system. As new time series values arrive, we send notifications to the application based on predefined time and accuracy constraints. All of our optimization approaches intend to increase the efficiency of forecast queries while ensuring high forecast accuracy.
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Landbris, Johan. "A Non-functional evaluation of NoSQL Database Management Systems." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-46804.
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NoSQL is basically a family name for all Database Management Systems (DBMS) that is not Relational DBMS. The fast growth of all social networks has led to a huge amount of unstructured data that NoSQL DBMS is supposed to handle better than Relational DBMS. Most comparisons performed are between Relational DBMS and NoSQL DBMS. In this paper, the comparison is about non-functional properties for different types of NoSQL DBMS instead. Three of the most common NoSQL types are Document Stores, Key-Value Stores and Column Stores. The most used DBMS of those types are MongoDB, Redis and Apache Cassandra. After working with the databases and performing YCSB Benchmarking the conclusion is that if the database should handle an enormous amount of data, Cassandra is most probably best choice. If speed is the most important property and if all data fits within the memory; Redis is probably the most well suited database. If the database needs to be flexible and versatile, MongoDB is probably the best choice.
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Clark, Allan M. "A framework for monitoring resources in database management systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ36015.pdf.
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Chaudhri, Akmal Bashir. "A systematic performance study of object database management systems." Thesis, City University London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243885.
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Floratos, Sofoklis. "High Performance Iterative Processing in Relational Database Management Systems." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1605909940057503.
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Moolman, George Christiaan. "A relational database management systems approach to system design." Thesis, Virginia Tech, 1992. http://hdl.handle.net/10919/43628.
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Systems are developed to fulfill certain requirements. Several system design configurations usually can fulfill the technical requirements, but at different equivalent life-cycle costs. The problem is how to manipulate and evaluate different system configurations so that the required system effectiveness can be achieved at a minimum equivalent cost. It is also important to have a good definition of all the major consequences of each design configuration. For each alternative configuration considered, it is useful to know the number of units to deploy, the inventory and other logistic requirements, as well as the sensitivity of the system to changes in input variable values.
An intelligent relational database management system is defined to solve the problem described. Table structures are defined to maintain the required data elements and algorithms are constructed to manipulate the data to provide the necessary information. The methodology is as follows: Customer requirements are analyzed in functional terms. Feasible design alternatives are considered and defined as system design configurations. The reliability characteristics of each system configuration are determined, initially from a system-level allocation, and later determined from test and evaluation data. A maintenance analysis is conducted to determine the inventory requirements (using reliability data) and the other logistic requirements for each design configuration. A vector of effectiveness measures can be developed for each customer, depending on objectives, constraints, and risks. These effectiveness measures, consisting of a combination of performance and cost measures, are used to aid in objectively deciding which alternative is preferred.
Relationships are defined between the user requirements, the reliability and maintainability of the system, the number of units deployed, the inventory level, and other logistic characteristics of the system. A heuristic procedure is developed to interactively manipulate these parameters to obtain a good solution to the problem with technical performance and cost measures as criteria. Although it is not guaranteed that the optimal solution will be found, a feasible solution close to the optimal will be found. Eventually the user will have, at any time, the ability to change the value of any parameter modeled. The impact on the total system will subsequently be made visible.<br>Master of Science
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Moolman, G. Chris. "A relational database management systems approach to system design /." This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-07102009-040421/.
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Lepinioti, Konstantina. "Data mining and database systems : integrating conceptual clustering with a relational database management system." Thesis, Bournemouth University, 2011. http://eprints.bournemouth.ac.uk/17765/.
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Many clustering algorithms have been developed and improved over the years to cater for large scale data clustering. However, much of this work has been in developing numeric based algorithms that use efficient summarisations to scale to large data sets. There is a growing need for scalable categorical clustering algorithms as, although numeric based algorithms can be adapted to categorical data, they do not always produce good results. This thesis presents a categorical conceptual clustering algorithm that can scale to large data sets using appropriate data summarisations. Data mining is distinguished from machine learning by the use of larger data sets that are often stored in database management systems (DBMSs). Many clustering algorithms require data to be extracted from the DBMS and reformatted for input to the algorithm. This thesis presents an approach that integrates conceptual clustering with a DBMS. The presented approach makes the algorithm main memory independent and supports on-line data mining.
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Sheth, Amit Pravin. "Adaptive concurrency control for distributed database systems /." The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487262513408523.
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Bryant, Miranda A. "Representing meaningful provenance in scientific workflow systems." Laramie, Wyo. : University of Wyoming, 2007. http://proquest.umi.com/pqdweb?did=1402176091&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.
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Jiao, Toni C. "Database development and intranet based image included database management system for ballistic firearm identification system." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2003. https://ro.ecu.edu.au/theses/1551.
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The process of imaging, collecting and searching a cartridge case to identifying its suspected firearm is a time consuming procedure. Within this study, a cartridge case identification database management system in an Intranet environment is designed and implemented, thus enabling firearm examiners from different forensic laboratories to engage firearm identification without the constraints of time and location. Specifically, the study investigates appropriate database management system for image involved and Intranet secured ballistics firearm identification database. The results demonstrated that a computerized firearm identification system could be implemented in Intranet with a secure, scalable, performable Intranet database management system.
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Xu, Zichen. "Power-Performance Tradeoffs in Database Systems." Scholar Commons, 2009. https://scholarcommons.usf.edu/etd/95.
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With the total energy consumption of computing systems increasing at a steep rate, much attention had been paid to the design of energy-efficient computing systems and applications. So far, database system design has focused on improving the performance of query processing. The objective of this study is to explore the potential of energy conservation in relational database management systems. The hypothesis is: by modifying the query optimizer in a Database management system (DBMS) to take the energy cost of query plans into consideration, we will be able to reduce the energy usage of database servers and control the tradeoffs between energy consumption and system performance. In this thesis, we provide an in-depth anatomy of typical queries in various benchmarks and qualitatively analyze the energy profile of such queries. The results of extensive experiments show that power savings in the range of 11% to 22% can be achieved by equipping the DBMS with a simple query optimizer that selects query plans based on both estimated processing time and energy requirements. We advocate more research efforts be invested into the design and evaluation of power-aware DBMSs in hope to reach higher level of energy efficiency.
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Agrawal, Tanu. "Fear and desire in systems design : negotiating database usefulness." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/42392.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2008.<br>Includes bibliographical references (p. 224-235).<br>Databases are ubiquitous. They are used for a host of functions including coordination, decision making, and memory archiving. Despite their importance and ubiquity, databases continue to frustrate us, often departing from the goals originally set for them. If databases are such essential ingredients for organizations, what diminishes their usefulness? Besides the nature of the data that is entered into the database, usefulness is also shaped by the fields, features, and functionalities that the database designers originally construct that then shape the kind of data that can be entered into the system. This dissertation examines the process of database design and the assumptions and concerns adopted by the stakeholders involved in it. I conducted a year long ethnographic study of a university that has been engaged in creating a self-sustaining Environment Health and Safety system to manage research related hazards and to ensure regulatory compliance. The integrated database system was envisioned as a tool that would allow the university to observe and improve compliance practices while keeping records that would be available for self-auditing and government inspection. My research observations suggest that actors imagine diverse purposes that the database, when complete, should serve. These purposes - entailing the three themes of accountability, efficiency and comparability - appear to guide the design process. As these imagined purposes gain momentum, they translate into both desires and fears for the features of the database. For instance, when efficiency is imagined as a purpose, it creates a desire for features such as drop-down menus that are easy enter information into. The inclusion of such features, however, creates a fear of oversimplification.<br>(cont.) Through a negotiated process, features such as text boxes are added to address the fears. Yet, every design change negotiated within the database system creates ripple effects with regard to other purposes, generating the need for still further changes. The process of database design becomes highly dynamic and the final database system is a negotiated compromise between multiple trade-offs over time. By juxtaposing these fears and desires, and through the use of causal-flow models, I articulate the process by which databases depart from their original goals.<br>by Tanu Agrawal.<br>Ph.D.
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Ritsch, Roland. "Optimization and evaluation of array queries in database management systems." [S.l. : s.n.], 1999. http://deposit.ddb.de/cgi-bin/dokserv?idn=959772502.
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