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Journal articles on the topic 'Databases Relational databases'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Tengeri, Dávid, and Ferenc Havasi. "Database Slicing on Relational Databases." Acta Cybernetica 21, no. 4 (2014): 629–53. http://dx.doi.org/10.14232/actacyb.21.4.2014.6.

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2

Finkelstein, S., M. Schkolnick, and P. Tiberio. "Physical database design for relational databases." ACM Transactions on Database Systems 13, no. 1 (1988): 91–128. http://dx.doi.org/10.1145/42201.42205.

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3

Nisa, Behjat U. "A Comparison between Relational Databases and NoSQL Databases." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 845–48. http://dx.doi.org/10.31142/ijtsrd11214.

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4

Maatuk, Abdelsalam, M. Akhtar Ali, and Nick Rossiter. "Converting Relational Databases into Object-relational Databases." Journal of Object Technology 9, no. 2 (2010): 145. http://dx.doi.org/10.5381/jot.2010.9.2.a3.

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5

., Vinay Goyal. "REENGINEERING OF RELATIONAL DATABASES TO OBJECTORIENTED DATABASE." International Journal of Research in Engineering and Technology 03, no. 01 (2014): 112–15. http://dx.doi.org/10.15623/ijret.2014.0301018.

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6

Garvey, M. "Relational databases." Information and Software Technology 34, no. 12 (1992): 825. http://dx.doi.org/10.1016/0950-5849(92)90125-9.

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7

NAVNEET KUMAR, KASHYAP, PANDEY B.K, MANDORIA H.L, and KUMAR ASHOK. "A REVIEW OF LEADING DATABASES: RELATIONAL and NON-RELATIONAL DATABASE." i-manager's Journal on Information Technology 5, no. 2 (2016): 34. http://dx.doi.org/10.26634/jit.5.2.6002.

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8

Bordoloi, Subhrajyoti, and Bichitra Kalita. "Designing Graph Database Models from Existing Relational Databases." International Journal of Computer Applications 74, no. 1 (2013): 25–31. http://dx.doi.org/10.5120/12850-9303.

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9

Qadah and Irani. "A Database Machine for Very Large Relational Databases." IEEE Transactions on Computers C-34, no. 11 (1985): 1015–25. http://dx.doi.org/10.1109/tc.1985.1676534.

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10

Thakur, Nimesh, and Nishi Gupta. "Relational and Non Relational Databases: A Review." Journal of University of Shanghai for Science and Technology 23, no. 08 (2021): 117–21. http://dx.doi.org/10.51201/jusst/21/08341.

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Relational and non-relational databases are the two types of databases that are used to store data and perform dierent operations on it. For data storage, they use a variety of formats. In this paper, we’ll try to gure out what they’re all about and what the main dierences are. Databases serve as a data centre from which information is collected and processed. Data science is a multidisciplinary eld that combines mathematics, statistics, and programming to research data. For a data scientist, a basic understanding of databases is a must-have ability. We’ll look at how a data scientist can make

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11

Sharma, Yashraj, and Yashasvi Sharma. "CASE STUDY OF TRADITIONAL RDBMS AND NOSQL DATABASE SYSTEM." International Journal of Research -GRANTHAALAYAH 7, no. 7 (2019): 351–59. http://dx.doi.org/10.29121/granthaalayah.v7.i7.2019.777.

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On the basis of reliability, rational models are useful but not in terms of systems which involve huge amount of data; in such cases, non-relational models are much more useful. To store large chunks of data, NoSQL databases are used. NoSQL databases are scalable and wide ranged because they are non-relationally distributed. In relational databases, it was not possible to manage data which involved very large number of Big Data applications hence the concept of NoSQL database was introduced. There are a lot of advantages of NoSQL which not only involve its own features but also som

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K.Rathva, Mayuree, and Sahani G.J. "Watermarking Relational Databases." International Journal of Computer Science, Engineering and Applications 3, no. 1 (2013): 71–79. http://dx.doi.org/10.5121/ijcsea.2013.3107.

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13

Yang, Xiaoyan, Cecilia M. Procopiuc, and Divesh Srivastava. "Summarizing relational databases." Proceedings of the VLDB Endowment 2, no. 1 (2009): 634–45. http://dx.doi.org/10.14778/1687627.1687699.

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14

Seltzer, Margo. "Beyond relational databases." Communications of the ACM 51, no. 7 (2008): 52–58. http://dx.doi.org/10.1145/1364782.1364797.

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15

Jackson, MS. "Beyond relational databases." Information and Software Technology 32, no. 4 (1990): 258–65. http://dx.doi.org/10.1016/0950-5849(90)90059-z.

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16

Seltzer, Margo. "Beyond Relational Databases." Queue 3, no. 3 (2005): 50–58. http://dx.doi.org/10.1145/1059791.1059807.

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17

Alekseev, Konstantin. "Relational database problems." Кибернетика и программирование, no. 2 (February 2020): 7–18. http://dx.doi.org/10.25136/2644-5522.2020.2.34076.

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The relevance of this article lies in the fact that today's databases are the basis of numerous information systems.&nbsp;The information accumulated in them is extremely valuable material, and today database processing methods are widely spread in terms of extracting additional methods, knowledge from them, which are interconnected with generalization and various additional methods of information processing.The object of research in this work is relational databases and DBMS, the subject of research is the features of their use in applied programming.In accordance with the set goal, it is

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18

Beech, David, and Çetin Özbütün. "Object databases as generalizations of relational databases." Computer Standards & Interfaces 13, no. 1-3 (1991): 221–30. http://dx.doi.org/10.1016/0920-5489(91)90030-4.

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19

Kunda, Douglas, and Hazael Phiri. "A Comparative Study of NoSQL and Relational Database." Zambia ICT Journal 1, no. 1 (2017): 1–4. http://dx.doi.org/10.33260/zictjournal.v1i1.8.

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Relational Database and NoSQL are competing types of database models. The former has been in existence since 1979 and the latter since the year 2000. The demands of modern applications especially in web 2.0, 3.0 and big data have made NoSQL a popular database of choice. Choosing an appropriate database model to use is an important decision that developers must make based on the features of a given database model. This paper compares the features of Relational Databases and NoSQL to establish which database is better at supporting demands of modern applications. The paper also brings out the ch

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20

Pokorný, Jaroslav. "Integration of Relational and NoSQL Databases." Vietnam Journal of Computer Science 06, no. 04 (2019): 389–405. http://dx.doi.org/10.1142/s2196888819500210.

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The analysis of relational and NoSQL databases leads to the conclusion that these data processing systems are to some extent complementary. In the current Big Data applications, especially where extensive analyses (so-called Big Analytics) are needed, it turns out that it is nontrivial to design an infrastructure involving data and software of both types. Unfortunately, the complementarity negatively influences integration possibilities of these data stores both at the data model and data processing levels. In terms of performance, it may be beneficial to use a polyglot persistence, a multimod

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21

Zhou, Peng, Mei Li, Jing Huang, and Hua Fang. "Research on Database Schema Comparison of Relational Databases and Key-Value Stores." Advanced Materials Research 1049-1050 (October 2014): 1860–63. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1860.

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With the rapid development of Internet technology, the management capacity of traditional relational databases becomes relatively inefficient when facing the access and processing of big data. As a kind of non-relational databases, the key-value stores, with its high scalability, provide an efficient solution to the problem. This article introduces the concept and features of Key-Value stores, and followed by the comparison with the traditional relational databases, and an example is illustrated to explain its typical application and finally the existing problems of Key-Value stores are summar

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22

Princz, Mária. "Trends and Challenges of Databases." International Journal of Engineering and Management Sciences 3, no. 5 (2018): 71–75. http://dx.doi.org/10.21791/ijems.2018.5.8.

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The database management, using relational databases, is part of curriculum in the Hungarian high schools. The aim of this paper is to present how we can show for students the challenges facing data processing, data retrieval, beyond the relational database management taught in high school.

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23

Abdullah, Ahmad, and Qingfeng Zhuge. "From Relational Databases to NoSQL Databases: Performance Evaluation." Research Journal of Applied Sciences, Engineering and Technology 11, no. 4 (2015): 434–39. http://dx.doi.org/10.19026/rjaset.11.1799.

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24

Alotaibi, Obaid, and Eric Pardede. "Transformation of Schema from Relational Database (RDB) to NoSQL Databases." Data 4, no. 4 (2019): 148. http://dx.doi.org/10.3390/data4040148.

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Relational database has been the de-facto database choice in most IT applications. In the last decade there has been increasing demand for applications that have to deal with massive and un-normalized data. To satisfy the demand, there is a big shift to use more relaxed databases in the form of NoSQL databases. Alongside with this shift, there is a need to have a structured methodology to transform existing data in relational database (RDB) to NoSQL database. The transformation from RDB to NoSQL database has become more challenging because there is no current standard on NoSQL database. The ai

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25

Karunaratna, Damitha D. "BUILDING ONTOLOGIES OVER RELATIONAL DATABASES." International Journal of Research -GRANTHAALAYAH 6, no. 11 (2018): 254–65. http://dx.doi.org/10.29121/granthaalayah.v6.i11.2018.1123.

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Relational Databases are typically created to fulfil the information requirements of a community of users generally belongs to a single organization. Data stored in these databases were typically accessed by using Structured Query Languages or through customized interfaces. With the popularity of the World Wide Web and the availability of large number of Relational Databases for public access there is a need for users to retrieve data from these databases by using a text-based queries, possibly by using the terms that they are familiar with. However, the inherent limitations of Structured Quer

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26

Chung, Jen-Yao, Yi-Jing Lin, and Daniel T. Chang. "Object and relational databases." ACM SIGPLAN OOPS Messenger 6, no. 4 (1995): 164–69. http://dx.doi.org/10.1145/260111.260273.

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27

Llorens, J., and A. Trénor. "MARC and relational databases." Electronic Library 11, no. 2 (1993): 93–96. http://dx.doi.org/10.1108/eb045213.

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28

Kocharekar, Raju. "Nulls in relational databases." ACM SIGMOD Record 18, no. 1 (1989): 68–73. http://dx.doi.org/10.1145/382272.382416.

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29

Arif, Dashne Raouf, and Nzar Abdulqadir Ali. "Improving the performance of big data databases." Kurdistan Journal of Applied Research 4, no. 2 (2019): 206–20. http://dx.doi.org/10.24017/science.2019.2.20.

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Real-time monitoring systems utilize two types of database, they are relational databases such as MySQL and non-relational databases such as MongoDB. A relational database management system (RDBMS) stores data in a structured format using rows and columns. It is relational because the values of the tables are connected. A non-relational database is a database that does not adopt the relational structure given by traditional. In recent years, this class of databases has also been referred to as Not only SQL (NoSQL). This paper discusses many comparisons that have been conducted on the execution

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30

Thomer, Andrea K., and Karen M. Wickett. "Relational data paradigms: What do we learn by taking the materiality of databases seriously?" Big Data & Society 7, no. 1 (2020): 205395172093483. http://dx.doi.org/10.1177/2053951720934838.

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Although databases have been well-defined and thoroughly discussed in the computer science literature, the actual users of databases often have varying definitions and expectations of this essential computational infrastructure. Systems administrators and computer science textbooks may expect databases to be instantiated in a small number of technologies (e.g., relational or graph-based database management systems), but there are numerous examples of databases in non-conventional or unexpected technologies, such as spreadsheets or other assemblages of files linked through code. Consequently, w

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31

Matallah, Houcine, Ghalem Belalem, and Karim Bouamrane. "Comparative Study Between the MySQL Relational Database and the MongoDB NoSQL Database." International Journal of Software Science and Computational Intelligence 13, no. 3 (2021): 38–63. http://dx.doi.org/10.4018/ijssci.2021070104.

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NoSQL databases are new architectures developed to remedy the various weaknesses that have affected relational databases in highly distributed systems such as cloud computing, social networks, electronic commerce. Several companies loyal to traditional relational SQL databases for several decades seek to switch to the new “NoSQL” databases to meet the new requirements related to the change of scale in data volumetry, the load increases, the diversity of types of data handled, and geographic distribution. This paper develops a comparative study in which the authors will evaluate the performance

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32

Lourenço, João Ricardo, Bruno Cabral, Jorge Bernardino, and Marco Vieira. "Comparing NoSQL Databases with a Relational Database: Performance and Space." Services Transactions on Big Data 2, no. 1 (2015): 1–14. http://dx.doi.org/10.29268/stbd.2015.2.1.1.

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33

Bouamama, Samah. "Migration from a Relational Database to NoSQL." International Journal of Knowledge-Based Organizations 8, no. 3 (2018): 63–80. http://dx.doi.org/10.4018/ijkbo.2018070104.

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This article describes how due to the monstrous evolution of the technology and the enormous increase in data, it becomes difficult to work with traditional database management tools; relational databases quickly reach their limits and adding servers does not increase performance. As a result of this problem, new technologies have emerged, such as NoSQL databases, which radically change the architecture of the databases that the authors are used to seeing, thus increasing the performance and availability of services. As these technologies are relatively new, standard or formal migration proces

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Ait El Mouden, Zakariyaa, and Abdeslam Jakimi. "A New Algorithm for Storing and Migrating Data Modelled by Graphs." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 11 (2020): 137. http://dx.doi.org/10.3991/ijoe.v16i11.15545.

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<span>NoSQL databases have moved from theoretical solutions to exceed relational databases limits to a practical and indisputable application for storing and manipulation big data. In term of variety, NoSQL databases store heterogeneous data without being obliged to respect a predefined schema such as the case of relational and object-relational databases. NoSQL solutions surpass the traditional databases in storage capacity; we consider MongoDB for example, which is a document-oriented database capable of storing unlimited number of documents with a maximal size of 32TB depending on the

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35

Wei, Ling Ling, and Wei Yang. "A Constructed Method of the Hash Function for the Rough Relational Databases." Applied Mechanics and Materials 427-429 (September 2013): 2588–91. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.2588.

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Rough relational database model provided a processing method for uncertainty data, So based on the Hash technology and the data characteristic of rough relational database, it was researched the multiple value data item in the rough relational database represented by binary string in virtue of equivalence classes, calculated its decimal value, and constructed Hash Function. Then according to the decimal number distributed Hash address where stored the data of the rough relational databases. Finally, an algorithm for constructed method of Hash function for the rough relational databases was des

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36

Ha, Van Muon, Yulia A. Shichkina, and Sergey V. Kostichev. "Determining the Composition of Collections for Key-Document Databases Based on a Given Set of Object Properties and Database Querie." Computer tools in education, no. 3 (September 30, 2019): 15–28. http://dx.doi.org/10.32603/2071-2340-2019-3-15-28.

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The work of transforming a database from one format periodically appears in different organizations for various reasons. Today, the mechanism for changing the format of relational databases is well developed. However, with the advent of new types of databases, such as NoSQL, this problem is prevalent due to the radically different ways of data organization at the various databases. This article discusses a formalized method based on set theory, at the choice of the number and composition of collections for a key-value type database. The initial data are the properties of objects, about which i

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37

Zhang, Xiao Lin, Wan Li Wang, and Xiao Qi Lv. "Research on Technology of Medical Image Database and its Connection with HIS Database." Advanced Materials Research 267 (June 2011): 119–23. http://dx.doi.org/10.4028/www.scientific.net/amr.267.119.

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Medical digital image information storage standard and existing heterogeneous database technology were analyzed with view to the particularity of the standard for medical images; data in medical images were organized according to data organizational hierarchy in the DICOM standard and sophisticated relational databases were utilized to store medical images. Using XML as a middleware to connect medical image database to HIS and then through relational databases and XML transformation rules to complete the conversion of the two databases into XML document. The study indicated that the method is

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38

Chung, Chin-Wan. "An interface between object-oriented databases and relational databases." Journal of Systems Integration 5, no. 3 (1995): 253–74. http://dx.doi.org/10.1007/bf01974951.

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39

Pokorny, Jaroslav. "Modelling of Graph Databases." Journal of Advanced Engineering and Computation 1, no. 1 (2017): 04. http://dx.doi.org/10.25073/jaec.201711.44.

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Comparing graph databases with traditional,e.g., relational databases, some important database features are often missing there. Particularly, a graph database schema including integrity constraints is mostly not explicitly defined, also a conceptual modelling is not used. It is hard to check a consistency of the graph database, because almost no integrity constraints are defined or only their very simple representatives can be specified. In the paper, we discuss these issues and present current possibilities and challenges in graph database modelling. We focus also on integrity constraints mo

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40

Imam, Abdullahi Abubakar, Shuib Basri, Rohiza Ahmad, et al. "DSP: Schema Design for Non-Relational Applications." Symmetry 12, no. 11 (2020): 1799. http://dx.doi.org/10.3390/sym12111799.

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The way a database schema is designed has a high impact on its performance in relational databases, which are symmetric in nature. While the problem of schema optimization is even more significant for NoSQL (“Not only SQL”) databases, existing modeling tools for relational databases are inadequate for this asymmetric setting. As a result, NoSQL modelers rely on rules of thumb to model schemas that require a high level of competence. Several studies have been conducted to address this problem; however, they are either proprietary, symmetrical, relationally dependent or post-design assessment to

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41

Khaidarova, Sapiahon. "CREATING SQL-QUERIES IN RELATIONAL DATABASES." RSUH/RGGU Bulletin. Series Information Science. Information Security. Mathematics, no. 3 (2020): 8–19. http://dx.doi.org/10.28995/2686-679x-2020-3-8-19.

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The article outlines the methods for creating SQL queries in relational databases. The use of the structured query language SQL in relational databases is substantiated. It provides information about the SQL standard and the three-tier database organization system. The author describes the choice of a data model based on the conceptual level using to that end an example of the Kokand Pedagogical Institute as the relational database model. A relational conceptual diagram of the information model of a pedagogical institute is compiled. Such a conceptual diagram is depicted using a cluster. Objec

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42

Pokorný, Jaroslav. "Integration of Relational and Graph Databases Functionally." Foundations of Computing and Decision Sciences 44, no. 4 (2019): 427–41. http://dx.doi.org/10.2478/fcds-2019-0021.

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Abstract In today’s multi-model database world there is an effort to integrate databases expressed in different data models. The aim of the article is to show possibilities of integration of relational and graph databases with the help of a functional data model and its formal language – a typed lambda calculus. We suppose the existence of a data schema both for the relational and graph database. In this approach, relations are considered as characteristic functions and property graphs as sets of single-valued and multivalued functions. Then it is possible to express a query over such integrat

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43

Keivani, Negin, Abdelsalam M. Maatuk, Shadi Aljawarneh, and Muhammad Akhtar Ali. "Towards the Maturity of Object-Relational Database Technology: Promises and Reality." International Journal of Technology Diffusion 6, no. 4 (2015): 1–19. http://dx.doi.org/10.4018/ijtd.2015100101.

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Object-relational technology provides a significant increase in scalability and flexibility over the traditional relational databases. The additional object-relational features are particularly satisfying for advanced database applications that relational database systems have experienced difficulties. The key factor to the success of object-relational database systems is their performance. This paper aims to review the promises of Object-Relational database systems, examine the reality, and how their promises may be fulfilled through unification with the relational technology. To investigate

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44

Zhu, Liang. "Processing Recommender Top-N Queries in Relational Databases." Journal of Software 10, no. 2 (2015): 162–71. http://dx.doi.org/10.17706/jsw.10.2.162-171.

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45

Chiang, Roger H. L., Terence M. Barron, and Veda C. Storey. "Reverse engineering of relational databases: Extraction of an EER model from a relational database." Data & Knowledge Engineering 12, no. 2 (1994): 107–42. http://dx.doi.org/10.1016/0169-023x(94)90011-6.

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46

Ahmad, Khaleel, Mohammad Shoaib Alam, and Nur Izura Udzir. "Security of NoSQL Database Against Intruders." Recent Patents on Engineering 13, no. 1 (2019): 5–12. http://dx.doi.org/10.2174/1872212112666180731114714.

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Background: The evolution of distributed web-based applications and cloud computing has brought about the demand to store a large amount of big data in distributed databases. Such efficient systems offer excessive availability and scalability to users. The new type of database resolves many new challenges especially in large-scale and high concurrency applications which are not present in the relational database. NoSQL refers to non-relational databases that are different from the Relational Database Management System. Objective: NoSQL has many features over traditional databases such as high

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Aftab, Zain, Waheed Iqbal, Khaled Mohamad Almustafa, Faisal Bukhari, and Muhammad Abdullah. "Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping." Scientific Programming 2020 (July 1, 2020): 1–13. http://dx.doi.org/10.1155/2020/8813350.

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Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL d

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48

Pistol, Luminita, and Radu BUCEA-MANEA-TONIS. "Logical Querying of Relational Databases." Journal of Economic Development, Environment and People 5, no. 4 (2016): 58. http://dx.doi.org/10.26458/jedep.v5i4.518.

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This paper aims to demonstrate the usefulness of formal logic and lambda calculus in database programming. After a short introduction in propositional and first order logic, we implement dynamically a small database and translate some SQL queries in filtered java 8 streams, enhanced with Tuples facilities from jOOλ library.

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Deagustini, Cristhian Ariel David, Santiago Emanuel Fulladoza Dalibón, Sebastián Gottifredi, Marcelo Alejandro Falappa, Carlos Iván Chesñevar, and Guillermo Ricardo Simari. "Defeasible argumentation over relational databases." Argument & Computation 8, no. 1 (2017): 35–59. http://dx.doi.org/10.3233/aac-170017.

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Tinelli, Eufemia, Francesco M. Donini, and Eugenio Di Sciascio. "Compiling subsumption to relational databases." Intelligenza Artificiale 7, no. 1 (2013): 19–29. http://dx.doi.org/10.3233/ia-130044.

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