Relevant bibliographies by topics / Database Management System (DBMS)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Database Management System (DBMS)'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Database Management System (DBMS)"

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Van Aken, Dana, Dongsheng Yang, Sebastien Brillard, Ari Fiorino, Bohan Zhang, Christian Bilien, and Andrew Pavlo. "An inquiry into machine learning-based automatic configuration tuning services on real-world database management systems." Proceedings of the VLDB Endowment 14, no. 7 (March 2021): 1241–53. http://dx.doi.org/10.14778/3450980.3450992.

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Modern database management systems (DBMS) expose dozens of configurable knobs that control their runtime behavior. Setting these knobs correctly for an application's workload can improve the performance and efficiency of the DBMS. But because of their complexity, tuning a DBMS often requires considerable effort from experienced database administrators (DBAs). Recent work on automated tuning methods using machine learning (ML) have shown to achieve better performance compared with expert DBAs. These ML-based methods, however, were evaluated on synthetic workloads with limited tuning opportunities, and thus it is unknown whether they provide the same benefit in a production environment. To better understand ML-based tuning, we conducted a thorough evaluation of ML-based DBMS knob tuning methods on an enterprise database application. We use the OtterTune tuning service to compare three state-of-the-art ML algorithms on an Oracle installation with a real workload trace. Our results with OtterTune show that these algorithms generate knob configurations that improve performance by 45% over enterprise-grade configurations. We also identify deployment and measurement issues that were overlooked by previous research in automated DBMS tuning services.
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Győrödi, Cornelia A., Diana V. Dumşe-Burescu, Doina R. Zmaranda, Robert Ş. Győrödi, Gianina A. Gabor, and George D. Pecherle. "Performance Analysis of NoSQL and Relational Databases with CouchDB and MySQL for Application’s Data Storage." Applied Sciences 10, no. 23 (November 28, 2020): 8524. http://dx.doi.org/10.3390/app10238524.

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In the current context of emerging several types of database systems (relational and non-relational), choosing the type and database system for storing large amounts of data in today’s big data applications has become an important challenge. In this paper, we aimed to provide a comparative evaluation of two popular open-source database management systems (DBMSs): MySQL as a relational DBMS and, more recently, as a non-relational DBMS, and CouchDB as a non-relational DBMS. This comparison was based on performance evaluation of CRUD (CREATE, READ, UPDATE, DELETE) operations for different amounts of data to show how these two databases could be modeled and used in an application and highlight the differences in the response time and complexity. The main objective of the paper was to make a comparative analysis of the impact that each specific DBMS has on application performance when carrying out CRUD requests. To perform the analysis and to ensure the consistency of tests, two similar applications were developed in Java, one using MySQL and the other one using CouchDB database; these applications were further used to evaluate the time responses for each database technology on the same CRUD operations on the database. Finally, a comprehensive discussion based on the results of the analysis was performed that centered on the results obtained and several conclusions were revealed. Advantages and drawbacks for each DBMS are outlined to support a decision for choosing a specific type of DBMS that could be used in a big data application.
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Liu, Fan Ming, Xing Wei, and Fang Ming Li. "Structure Design of the Database in the INS/Database Matching Navigation System." Advanced Materials Research 760-762 (September 2013): 1930–35. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1930.

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Using the geophysical field data matching navigation could improve the concealment of the underwater vehicle, and it is also an important navigation technology in the future. Using the database to save the navigation data not only could overcome the drawbacks when using the files to storage the data but also integrated the different database together. The QNX Database is used to be the database management system (DBMS) of the INS/Database matching navigation system. According to the needs of the INS/Database matching navigation system and the relationship of the geophysical field data, the structure of geophysical field data database is designed and implemented. The result shows that the DBMS has well real-time performance, reliability and scalability. It meets the requirements of the DBMS.
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Ansari, Sakil Ahmad, and Jaychand Vishwakarma. "Survey on Database Concurrency Control in Multilevel Secure Database Management Systems." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 4 (April 30, 2018): 105. http://dx.doi.org/10.23956/ijarcsse.v8i4.645.

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Transactions are vital for database management systems (DBMSs) because they provide transparency to concurrency and failure. Concurrent execution of transactions may lead to contention for access to data, which in a multilevel secure DBMS (MLSIDBMS) may lead to insecurity. In this paper we examine security issues involved in database concurrency control for MLS/DBMSs and show how a scheduler can affect security. We introduce Data Conflict Security; (DC-Security) a property that implies a system is free of convert channels due to contention for access to data. We present a definition of DC Security based on noninterference. Two properties that constitute a necessary condition for DC-Security are introduced along with two other simpler necessary conditions. We have identified a class of schedulers we call Output-State-Equivalent for which another criterion implies DC-Security. The criterion considers separately the behavior of the scheduler in response to those inputs that cause rollback and those that do not. We characterize the security properties of several existing scheduling protocols and find many to be insecure
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Mohd Yunus, Mohd Amin, Sonniaa K. V. Gopala Krishnan, Nazri Mohd Nawi, and Ely Salwana Mat Surin. "Study on Database Management System Security Issues." JOIV : International Journal on Informatics Visualization 1, no. 4-2 (November 30, 2017): 192. http://dx.doi.org/10.30630/joiv.1.4-2.76.

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The study is about the security system of database management (DBMS) and proposed method. Information is an essential element in database management system where the users trust service providers will have a secure system to protect and prevent their information from malicious attack or stealing information. There are few types of technique applied to enhance the database security level.
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Vishwakarma, Jaychand, and Abhishek Shukla. "Survey on Security Issues and Their Techniques in DBMS." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 1 (January 30, 2018): 124. http://dx.doi.org/10.23956/ijarcsse.v8i1.544.

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Nowadays a Database security has become an important issue in technical world. The main objective of database security is to forbid unnecessary information exposure and modification data while ensuring the availability of the needed services. A numbers of security methods have been created for protecting the databases. Many security models have been developed based on different security aspects of database. All of these security methods are useful only when the database management system is designed and developing for protecting the database. Recently the growth of web application with database at its backend Secure Database Management System is more essential than only a Secure Database. Therefore this paper highlight on the Threats, Security Methods and Vulnerabilities in Database Management System with the help of survey performed on the field of secure databases.
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TRIGANO, PHILIPPE, JEAN-PAUL BARTHES, CATHERINE GREBOVAL, and FRANÇOIS VALLERNAUD. "QUERYING AN OBJECT-ORIENTED DATABASE USING FREE LANGUAGE." International Journal of Pattern Recognition and Artificial Intelligence 04, no. 03 (September 1990): 429–45. http://dx.doi.org/10.1142/s0218001490000265.

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A man-machine interface in natural language for a DataBase Management System (DBMS) called VORAS, based upon semantics, is presented. This DBMS can also be used for knowledge representation, and is well-suited to the design of queries in natural language. The system VORAS is an object-oriented DBMS developed from a specific model of representation called the Property Driven Model (PDM). A user may write a query in natural language. Most of the analysis is done at a semantic level. A syntactic level has been added, to improve the performance of the system. However, it is still possible to use a short-hand style.
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Anjard, Ronald P. "The Basics of Database Management Systems (DBMS)." Industrial Management & Data Systems 94, no. 5 (June 1994): 11–15. http://dx.doi.org/10.1108/02635579410063261.

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Koishibayev, Timur, and Zhanat Umarova. "Cryptanalysis of Password Protection of Oracle Database Management System (DBMS)." Journal of Physics: Conference Series 710 (April 2016): 012003. http://dx.doi.org/10.1088/1742-6596/710/1/012003.

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O., Orlunwo Placida, and Prince Oghenekaro A. "DISTRIBUTED DATABASE MANAGEMENT SYSTEM (DBMS) ARCHITECTURES AND DISTRIBUTED DATA INDEPENDENCE." International Journal of Computer Science and Mobile Computing 10, no. 1 (January 28, 2021): 23–48. http://dx.doi.org/10.47760/ijcsmc.2021.v10i01.004.

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Dissertations / Theses on the topic "Database Management System (DBMS)"

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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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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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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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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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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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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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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.

The choice of the programming tools is individual and particular.

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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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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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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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Books on the topic "Database Management System (DBMS)"

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Malcher, Michelle. Oracle database administration for Microsoft SQL server DBAs. New York: Oracle Press/McGraw-Hill, 2011.

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Anderson, Mark. Microsoft SQL server 2008 administration for Oracle DBAs. New York: McGraw-Hill Osborne Media, 2010.

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Windows multi-DBMS programming: Using C++, Visual Basic, ODBC, OLE2, and tools for DBMS projects. New York: Wiley, 1995.

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SQL solutions for IBM DBMS. New York: Van Nostrand Reinhold, 1991.

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Database system concepts. 6th ed. Dubuque, IA: McGraw-Hill Companies, 2011.

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F, Korth Henry, and Sudarshan S, eds. Database system concepts. 3rd ed. Boston, Mass: WCB/McGraw-Hill, 1999.

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Silberschatz, Abraham. Database system concepts. 3rd ed. New York: McGraw-Hill, 1997.

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F, Korth Henry, and Sudarshan S, eds. Database system concepts. 4th ed. Boston: McGraw-Hill, 2002.

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F, Korth Henry, and Sudarshan S, eds. Database system concepts. 5th ed. Maidenhead: McGraw-Hill, 2005.

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Rosenfeld, Pilar N. Investigation of DBMS for use in a research environment. Santa Monica, CA (P.O. Box 2138, Santa Monica 90406-2138): Rand Corp., 1985.

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Book chapters on the topic "Database Management System (DBMS)"

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Geisler, Sandra, and Christoph Quix. "Database Management Systems (DBMS)." In Encyclopedia of Big Data, 1–6. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-32001-4_538-1.

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Arcieri, Franco, Carmine Cammino, Enrico Nardelli, Maurizio Talamo, and Antonino Venza. "The Italian Cadastral Information System: A Real-Life Spatio-Temporal DBMS." In Spatio-Temporal Database Management, 79–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48344-6_5.

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Raper, Jonathan F., and Michael S. Bundock. "Implementation of a User Environment for a Spatial DBMS." In Geographic Database Management Systems, 18–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77605-2_3.

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McLeish, Mary, Matt Cecile, and Alex Lopez-Suarez. "Using a blackboard architecture in a distributed DBMS environment: An expert system application." In Statistical and Scientific Database Management, 236–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52342-1_32.

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Kacprzyk, Janusz, and Sławomir Zadrożny. "Fquery for Access: Fuzzy Querying for a Windows-Based DBMS." In Fuzziness in Database Management Systems, 415–33. Heidelberg: Physica-Verlag HD, 1995. http://dx.doi.org/10.1007/978-3-7908-1897-0_18.

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Cafarella, Michael, David DeWitt, Vijay Gadepally, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, and Matei Zaharia. "A Polystore Based Database Operating System (DBOS)." In Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 3–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71055-2_1.

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Weik, Martin H. "database management system." In Computer Science and Communications Dictionary, 340. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_4194.

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Helland, Pat. "Database Management System." In Encyclopedia of Database Systems, 957–62. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_662.

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Helland, Pat. "Database Management System." In Encyclopedia of Database Systems, 714–19. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_662.

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Helland, Pat. "Database Management System." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_662-2.

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Conference papers on the topic "Database Management System (DBMS)"

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Lustosa, Hermano, Fábio Porto, and Patrick Valduriez. "SAVIME: A Database Management System for Simulation Data Analysis and Visualization." In XXXIV Simpósio Brasileiro de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbbd.2019.8810.

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Limitations in current DBMSs prevent their wide adoption in scientific applications. In order to make scientific applications benefit from DBMS support, enabling declarative data analysis and visualization over scientific data, we present an in-memory array DBMS system called SAVIME. In this work we describe the system SAVIME, along with its data model. Our preliminary evaluation shows how SAVIME, by using a simple storage definition language (SDL) can outperform the state-of-the-art array database system, SciDB, during the process of data ingestion. We also show that is possible to use SAVIME as a storage alternative for a numerical solver without affecting its scalability.
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Helinda, Ayu, Zuhar Musliyana, Desita Ria Yusian TB, Mahendar Dwipayana, Julinawati Suanda, and Atikah Nor Johari. "Performance analysis of heterogeneous database management system (DBMS) synchronization using message digest 5." In PROCEEDINGS OF ADVANCED MATERIAL, ENGINEERING & TECHNOLOGY. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0027970.

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Gomes, Carlos, Eduardo Tavares, and Meuse Nogueira De O. Junior. "Energy Consumption Evaluation of NoSQL DBMSs." In XV Workshop em Desempenho de Sistemas Computacionais e de Comunicação. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/wperformance.2016.9729.

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Over the years, NoSQL Database Management Systems (DBMS) have been adopted as an alternative to the constraints of relational/SQL DBMSs. In order to demonstrate their feasibility, works have evaluated NoSQL DBMSs regarding some performance metrics, but energy consumption has not been assessed. Indeed, energy consumption is an issue that should not be neglected due to the rise of energy costs and environmental sustainability. This paper presents a peformance and energy consumption evaluation of NoSQL DBMSs, more specifically, Cassandra (column), MongoDB (document-oriented), Redis (key-value). Experiments are based on YCSB benchmark, and results demonstrate energy consumption can vary significantly among the assessed DBMSs for different commands (e.g., read) and workloads.
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Niebur, Glen L., and Thomas R. Chase. "A Grammar Driven Data Translation System for Computer Integrated Manufacturing." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/eim-1419.

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Abstract Integration of engineering software continues to be an important topic in mechanical design and manufacturing. One integration technique which has been proposed is to store a complete product representation in a single database using a database management system. In order to integrate existing CAE applications which are not designed for use with a DBMS, a method for importing and exporting data to the database is needed. A system for recognizing and translating a large class of engineering data, those data formats which can be described by regular grammars, is proposed.
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Hirano, Takato, Yutaka Kawai, and Yoshihiro Koseki. "DBMS-Friendly Searchable Symmetric Encryption: Constructing Index Generation Suitable for Database Management Systems." In 2021 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2021. http://dx.doi.org/10.1109/dsc49826.2021.9346255.

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Gourishankar, Yamini, and Frank Weisgerber. "Automation of Wind Pressure Computation Using a Data Management Approach." In ASME 1993 International Computers in Engineering Conference and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/edm1993-0107.

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Abstract It is observed that calculating the wind pressures on structures involves more data retrieval from the ASCE standard than any subjective reasoning on the designer’s part. Once the initial design requirements are established, the procedure involved in the computation is straightforward. This paper discusses an approach to automate the process associated with wind pressure computation on one story and multi-story buildings using a data management strategy (implemented using the ORACLE database management system). In the prototype system developed herein, the designer supplies the design requirements in the form of the structure’s exposure type, its dimensions and the nature of occupancy of the structure. Using these requirements, the program retrieves the necessary standards data from an independently maintained database, and computes the wind pressures. The final output contains the wind pressures on the main wind force resisting system, and on the components and claddings, for wind blowing parallel and perpendicular to the ridge. The knowledge encoded in the system was gained from ASCE codes, design guidelines and as a result of interviews with various experts and practitioners. Several information modeling methodologies such as the entity relationship model, IDEF 1X, etc. were employed in the system analysis and design phase of this project. The prototype is implemented on an IBM PC using the ORACLE DBMS and the ‘C’ programming language. Appendix A illustrates a sample run.
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Jung, Se-Kwon, Joseph Harrold, and Nawar Alchaar. "Application of a Large-Scale Database System for the Analysis and Design of the US EPR™ Standard Nuclear Power Plant." In ASME 2012 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/pvp2012-78373.

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Due to the increased size and complexity of large-scale commercial and industrial structures, it is increasingly challenging to manage key engineering data including analysis and design results of these structures. This paper presents a novel approach of using large-scale database systems as a means to gather, organize and manage key analysis and design results of a large-scale structure. Specifically, this paper describes in detail the development process of the backend database management system (DBMS) for the U.S. EPR™ Standard Nuclear Power Plant (NPP) Nuclear Island (NI) structures. The database system consists of three parent database tables to represent three representative groups of load combinations applicable to the U.S. EPR™ Standard NPP. Inheriting all characteristics of an applicable parent table, a primary child table in the database system represents a particular U.S. EPR™ NI Safety-Related structure in its entirety while a secondary child table a group of slabs or walls of the structure. Each secondary table is comprised of database fields that are representative of various structural demands, section capacities, reinforcing ratios, and demand-to-capacity ratios for three reinforced concrete design conditions (i.e., combined axial force and bending design, in-plane shear design, and out-of-plane shear design). The complete database system with fully populated tables is a central repository where all analysis and design results for the U.S. EPR™ NI Common Basemat structures are stored and sorted. To facilitate data queries from the developed backend database system, this paper introduces a user-friendly frontend interface program developed using Visual Basic Application (VBA) with Excel. Potential benefits of the developed database system are demonstrated with simple application examples involving simple data queries only followed by complex engineering tasks that require a more advanced form of data queries.
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Armas, Joseph, Patricio Navas, Tatiana Mayorga, Paola Rengifo, and Byron Arevalo. "Optimization of code lines and time of access to information through object-relational mapping (ORM) using alternative tools of connection to database management systems (DBMS)." In 2017 2nd International Conference on System Reliability and Safety (ICSRS). IEEE, 2017. http://dx.doi.org/10.1109/icsrs.2017.8272872.

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De Souza, Erico, and Edjander Mota. "DBMS for Web: The Future of Database Management." In 2006 IEEE International Conference on Information Reuse & Integration. IEEE, 2006. http://dx.doi.org/10.1109/iri.2006.252378.

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Zhang, W. J., Q. Li, and S. K. Tso. "A Comprehensive Study of Instance-As-Type Phenomenon in Product Date Modelling." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/eim-9017.

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Abstract This paper presents a comprehensive discussion of the Instance-As-Type (IAT) phenomenon that is observed in the development of complex engineering/product design databases. Basically, IAT reflects a kind of data dependency in databases; in particular it means that a data object appears both in the form of a type and in the form of an instance. As it is well known, uncontrolled data dependencies may lead to information inconsistency and thus severely affect the effectiveness of the product development process. It is therefore very important to develop strategies to cope with IAT in the design of complex engineering databases. The contributions of this paper lie in several aspects. It has provided a more comprehensive description of IAT, including an argument that IAT is in fact not a kind of data redundancy but data dependency. It has also clarified the two and only two feasible strategies for dealing with IAT, i.e., one making IAT absent in a database (strategy 1) and the other preserving IAT by providing a means to control it (strategy 2). The advantages and disadvantages associated with these two strategies have been discussed. Finally, this paper has pointed out that the implementation of strategy 2 can be realized by using general-purpose database management systems (DBMSs) by developing an enhanced program module. A general way to implement this module has also been outlined.
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Reports on the topic "Database Management System (DBMS)"

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Lum, Vincent Y., and Klaus Meyer-Wegener. A Conceptual Design of a Multimedia DBMS (Database Management System) for Advanced Applications. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada199548.

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Leishman, N. L. Management Information Database System. Office of Scientific and Technical Information (OSTI), May 1989. http://dx.doi.org/10.2172/6004600.

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Meyer-Wegener, Klaus, Vincent Y. Lum, and C. T. Wu. Image Database Management in a Multimedia System. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada199561.

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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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Widing, M. A., D. W. Blodgett, M. D. Braun, M. J. Jusko, J. M. Keisler, R. J. Love, and G. L. Robinson. DOE technology information management system database study report. Office of Scientific and Technical Information (OSTI), November 1994. http://dx.doi.org/10.2172/161564.

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Purvy, B., A. Daniel, M. Sinykin, and J. Smith. Relational Database Management System (RDBMS) Management Information Base (MIB) using SMIv2. Edited by D. Brower. RFC Editor, August 1994. http://dx.doi.org/10.17487/rfc1697.

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Mears, Brad. Advanced Traffic Management Systems (ATMS) Research Analysis Database System. Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada388177.

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Spencer, S. G. System configuration management plan for the TWRS controlled baseline database system [TCBD]. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/362420.

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ENGINEERING-SCIENCE INC DENVER CO. Trusted Database Management System. Interpretation of the Trusted Computer System Evaluation Criteria. Fort Belvoir, VA: Defense Technical Information Center, April 1991. http://dx.doi.org/10.21236/ada385759.

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Herbschleb, J., and P. M. Maurenbrecher. The engineering geology 'INGEOBASE' relational database management system for Amsterdam. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1994. http://dx.doi.org/10.4095/193959.

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