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1
Content available Big problems with Big Data
EN
The article presents an overview of the most important issues related to the phenomenon called big data. The characteristics of big data concerning the data itself and the data sources are presented. Then, the big data life cycle concept is formulated. The next sections focus on two big data technologies: MapReduce for big data processing and NoSQL databases for big data storage.
EN
Digitalization is currently the key factor for progress, with a rising need for storing, collecting, and processing large amounts of data. In this context, NoSQL databases have become a popular storage solution, each specialized on a specific type of data. Next to that, the multi-model approach is designed to combine benefits from different types of databases, supporting several models for data. Despite its versatility, a multi-model database might not always be the best option, due to the risk of worse performance comparing to the single-model variants. It is hence crucial for software engineers to have access to benchmarks comparing the performance of multi-model and single-model variants. Moreover, in the current Big Data era, it is important to have cluster infrastructure considered within the benchmarks. In this paper, we aim to examine how the multi-model approach performs compared to its single-model variants. To this end, we compare the OrientDB multi-model database with the Neo4j graph database and the MongoDB document store. We do so in the cluster setup, to enhance state of the art in database benchmarks, which is not yet giving much insight into cluster-operating database performance.
EN
In this paper, the authors attempt to identify the universal factors of the effectiveness of selected database models used in Management Information Systems. Selection of an appropriate database model at the stage of design and implementation directly determines the effectiveness of the Management Information Systems within an organisation. The relational database model and database models based on NoSQL paradigms, including in particular graph databases and document-oriented databases, will be evaluated. NoSQL-class database models demonstrate properties in terms of effective application for business purposes.
EN
Electric vehicles are increasingly popular means of transport. One of the most important problems of their operation is to optimize the use of a battery pack. It requires to analyze the operational characteristics of a vehicle in motion, which are stored in a database. If the measurement data are collected from many vehicles, the efficiency of their analysis is important. The objective of this article is to study the possibilities of using modern column-oriented databases in order to increase the efficiency of the analysis of selected operational characteristics of an electric vehicle. The research problem is a comparative analysis of the processing efficiency of selected measurement characteristics of an electric vehicle in relational and column-oriented data structures. Important analytical functions were formulated and recorded in the form of database queries. An experiment consisting in multiple execution of functions packages on various database structures, including a column-oriented one, was carried out. The execution time of packages and the IT system load were collected and analyzed. The analysis of the experiment results allows to conclude that the use of the column-oriented data structures made it possible to shorten the time of executing the functions analyzing the energy consumption by the electric vehicle’s drive system. Depending on the type of the analyzed characteristics of the vehicle and its method of representation in the database, a significant reduction of the analysis time compared to the relational structure was obtained. Also, a decrease in the load on the computer system during data processing on the column-oriented structures was noted. The use of the column-oriented databases in the processing and analysis of measurement operational characteristics of electric vehicles is justified and it can bring measurable effects. It should be considered that the effectiveness of solving depends on the number of the analyzed characteristics and the format of their representation in the computer.
EN
NoSQL databases boldly step into the area reserved so far for relational databases. NoSQL databases are more flexible than relational ones at cost of some disadvantages related especially with security and integrity constraints. The most convenient way to access a relational database in modern object applications are object-relational mapping tools. It turns out that some of these tools offer mappings to broad spectrum of NoSQL and object databases and text files. The aim of this article is to present this kind of tools and answer the question if they are really universal i.e. if they allow to persist, in any form, the same object entity as defined at the level of an object application.
PL
Bazy danych NoSQL coraz śmielej wkraczają na obszary zarezerwowane do tej pory dla relacyjnych baz danych. Bazy takie są bardziej elastyczne od baz relacyjnych, co okupione jest pewnymi wadami, związanymi szczególnie z bezpieczeństwem i więzami integralności. W dzisiejszych aplikacjach obiektowych najwygodniejszym sposobem dostępu do relacyjnej bazy danych jest zastosowanie narzędzi odwzorowania obiektowo-relacyjnego. Okazuje się, że niektóre z tych narzędzi oferują również odwzorowanie do szerokiej gamy baz NoSQL, baz obiektowych oraz plików tekstowych. Celem artykułu jest zaprezentowanie tego typu narzędzi i odpowiedź na pytanie, do jakiego stopnia są one uniwersalne, tzn. czy pozwalają tę samą encję trwałą zdefiniowaną na poziomie aplikacji obiektowej utrwalić w dowolny sposób.
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