scholarly journals Relational database problems

2020 ◽  
pp. 7-18
Author(s):  
Konstantin Alekseev
Keyword(s):  
Information Systems ◽  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
Heuristic Methods ◽  
Storage Medium ◽  
Database Structure ◽  
Slow Decline ◽  
The Subject ◽  
Over Time

The relevance of this article lies in the fact that today's databases are the basis of numerous information systems. 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 necessary to solve the following tasks:1) to consider the concept and essence of a relational database;2) to analyze the problematic aspects of relational databases in modern conditions. Relational databases are among the most widespread due to their simplicity and clarity at the creation stage and at the user level. It should also be noted that the main advantage of RDB is its compatibility with the main query language SQL, which is intuitive for users.Nevertheless, with all the variety of approaches, there are still some canons, violation of which greatly affects both the design of the database and its operation. For example, the problem of database normalization is very relevant. Neglecting normalization makes the database structure confusing and the database itself unreliable.Promising directions include the development of queries to a relational database using heuristic methods, as well as the method of accumulating previously optimized queries with subsequent verification of the derivability of the current query from the accumulated ones.Finally, a very slow decline in relational databases is probably happening. While they are still the primary storage medium, especially in large enterprise projects, they are gradually being replaced by non-relational solutions that will become the majority over time.

CREATING SQL-QUERIES IN RELATIONAL DATABASES

2020 ◽  
pp. 8-19
Author(s):  
Sapiahon Khaidarova ◽  
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Relational Databases ◽  
Query Language ◽  
Information Model ◽  
Subject Area ◽  
Conceptual Level ◽  
Microsoft Access ◽  
Pedagogical Institute ◽  
The Subject

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. Objects of the subject area are depicted in the form of tables, which differ from each other in geometric shapes or colors. The relationships between tables in Microsoft Access are presented. The basic rules for creating and filling tables in SQL using the instructions CREATE TABLE and INSERT INTO are considered. The syntax of the SELECT statement is given. All offers of the SELECT statement and their order are listed. Examples are given for compiling simple queries and subqueries in SQL using the SELECT statement for the database of the Kokand Pedagogical Institute. Information about the order of execution of internal and external requests is given. The article considers the ORDER BY offer of a SELECT statement for sorting query results.

scholarly journals DBTagger

2021 ◽  
Vol 14 (5) ◽  
pp. 813-821
Author(s):  
Arif Usta ◽  
Akifhan Karakayali ◽  
Özgür Ulusoy
Keyword(s):  
Deep Learning ◽  
Natural Language ◽  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
State Of The Art ◽  
Independent Solution ◽  
Rule Based ◽  
Mapping Problem ◽  
Stop Word

Translating Natural Language Queries (NLQs) to Structured Query Language (SQL) in interfaces deployed in relational databases is a challenging task, which has been widely studied in database community recently. Conventional rule based systems utilize series of solutions as a pipeline to deal with each step of this task, namely stop word filtering, tokenization, stemming/lemmatization, parsing, tagging, and translation. Recent works have mostly focused on the translation step overlooking the earlier steps by using adhoc solutions. In the pipeline, one of the most critical and challenging problems is keyword mapping; constructing a mapping between tokens in the query and relational database elements (tables, attributes, values, etc.). We define the keyword mapping problem as a sequence tagging problem, and propose a novel deep learning based supervised approach that utilizes POS tags of NLQs. Our proposed approach, called DBTagger (DataBase Tagger), is an end-to-end and schema independent solution, which makes it practical for various relational databases. We evaluate our approach on eight different datasets, and report new state-of-the-art accuracy results, 92.4% on the average. Our results also indicate that DBTagger is faster than its counterparts up to 10000 times and scalable for bigger databases.

scholarly journals FORMALIZED REPRESENTATION FOR THE DATA MODEL WITH THE UNIVERSAL BASIS OF RELATIONS

2019 ◽  
pp. 453-460
Author(s):  
Vitalii I. Yesin ◽  
Mikolaj Karpinski ◽  
Maryna V. Yesina ◽  
Vladyslav V. Vilihura
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Relational Databases ◽  
Subject Domain ◽  
Dynamic Changes ◽  
Standard Data ◽  
The Subject ◽  
Logical Design ◽  
The Creation ◽  
Universal Standard

The goal of the article is to develop a universal (standard) data model that allows you to get rid of the need for a costly policy of doing extra work when developing new ones or transforming existing relational databases (RDBs) caused by dynamic changes in the subject domain (SD). The requirements for the developed data model were formulated. In accordance with the formulated requirements, the data model was synthesized. To simplify the process of creating relational database schemas an algorithm for transforming the description of the subject domain into the relations of the universal basis of the developed model was proposed. The scientific novelty of the obtained results is: a data model that, unlike known ones, allows us to simplify the creation of RDB schemas at the stage of logical design of relational databases, under the conditions of dynamic changes in subject domains, due to the introduced universal basis of relations, as a means of describing structures and the presentation of data for various SDs has been developed.

Business Rules in Databases

2005 ◽  
pp. 47-53
Author(s):  
Antonio Badia
Keyword(s):  
Information Systems ◽  
Relational Databases ◽  
Database Systems ◽  
Business Rules ◽  
Business Rule ◽  
The Subject ◽  
Entity Relationship ◽  
Definition Of ◽  
Definition Of Information ◽  
Exact Definition

Though informal, the concept of business rule is very important to the modeling and definition of information systems. Business rules are used to express many different aspects of the representation, manipulation and processing of data (Paton, 1999). However, perhaps due to its informal nature, business rules have been the subject of a limited body of research in academia. There is little agreement on the exact definition of business rule, on how to capture business rules in requirements specification (the most common conceptual models, entity-relationship and UML, have no proviso for capturing business rules), and, if captured at all, on how to express rules in database systems. Usually, business rules are implemented as triggers in relational databases. However, the concept of business rule is more versatile and may require the use of other tools.

The Berlin SPARQL Benchmark

2011 ◽  
pp. 81-103 ◽  
Author(s):  
Christian Bizer ◽  
Andreas Schultz
Keyword(s):  
Relational Database ◽  
Database Management ◽  
Relational Databases ◽  
Query Language ◽  
Storage Systems ◽  
Sparql Query ◽  
Use Case ◽  
Benchmark Experiment ◽  
Relational Database Management ◽  
Relational Database Management Systems

The SPARQL Query Language for RDF and the SPARQL Protocol for RDF are implemented by a growing number of storage systems and are used within enterprise and open Web settings. As SPARQL is taken up by the community, there is a growing need for benchmarks to compare the performance of storage systems that expose SPARQL endpoints via the SPARQL protocol. Such systems include native RDF stores as well as systems that rewrite SPARQL queries to SQL queries against non-RDF relational databases. This article introduces the Berlin SPARQL Benchmark (BSBM) for comparing the performance of native RDF stores with the performance of SPARQL-to-SQL rewriters across architectures. The benchmark is built around an e-commerce use case in which a set of products is offered by different vendors and consumers have posted reviews about products. The benchmark query mix emulates the search and navigation pattern of a consumer looking for a product. The article discusses the design of the BSBM benchmark and presents the results of a benchmark experiment comparing the performance of four popular RDF stores (Sesame, Virtuoso, Jena TDB, and Jena SDB) with the performance of two SPARQL-to-SQL rewriters (D2R Server and Virtuoso RDF Views) as well as the performance of two relational database management systems (MySQL and Virtuoso RDBMS).

scholarly journals Improving the performance of big data databases

2019 ◽  
Vol 4 (2) ◽  
pp. 206-220
Author(s):  
Dashne Raouf Arif ◽  
Nzar Abdulqadir Ali
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
Database Management System ◽  
Data Sets ◽  
Relational Database Management System ◽  
Nosql Database ◽  
Sql Database ◽  
Performance Results ◽  
Relational Database Management

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 time performance of types of databases (SQL and NoSQL). In SQL (Structured Query Language) databases different algorithms are used for inserting and updating data, such as indexing, bulk insert and multiple updating. However, in NoSQL different algorithms are used for inserting and updating operations such as default-indexing, batch insert, multiple updating and pipeline aggregation. As a result, firstly compared with related papers, this paper shows that the performance of both SQL and NoSQL can be improved. Secondly, performance can be dramatically improved for inserting and updating operations in the NoSQL database compared to the SQL database. To demonstrate the performance of the different algorithms for entering and updating data in SQL and NoSQL, this paper focuses on a different number of data sets and different performance results. The SQL part of the paper is conducted on 50,000 records to 3,000,000 records, while the NoSQL part of the paper is conducted on 50,000 to 16,000,000 documents (2GB) for NoSQL. In SQL, three million records are inserted within 606.53 seconds, while in NoSQL this number of documents is inserted within 67.87 seconds. For updating data, in SQL 300,000 records are updated within 271.17 seconds, while for NoSQL this number of documents is updated within just 46.02 seconds.  

scholarly journals A Comparative Study of NoSQL and Relational Database

2017 ◽  
Vol 1 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Douglas Kunda ◽  
Hazael Phiri
Keyword(s):  
Big Data ◽  
Web 2.0 ◽  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
The Other ◽  
Database Model ◽  
Nosql Database ◽  
Database Models ◽  
Year 2000

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 challenges of NoSQL. Finally, the paper concludes by determining whether Relational Databases would completely be replaced by NoSQL database models. The findings revealed that, Relational Databases are based on ACID model which emphasizes better consistency, security and offers a standard query language. However, Relational Databases have poor scalability, weak performance, cost more, face availability challenges when supporting large number of users and handle limited volume of data. NoSQL, on the other hand is based on the BASE model, which emphasizes greater scalability and provides a flexible schema, offers better performance, mostly open source, cheap but, lacks a standard query language and does not provide adequate security mechanisms. Both databases will continue to exist alongside each other with none being better than the other. The choice of the database to use will depend on the nature of the application being developed. Each database type has its own challenges and strengths, with relational database lacking of support for unstructured data while NoSQL lacks standardization and has poor security. Modern applications in web 2.0, 3.0 and big data are well suited to use NoSQL but, there are still many applications that rely on Relational Databases.

An Approach to Integrate Collections of Images and Relational Databases

1988 ◽  
Vol 27 (04) ◽  
pp. 177-183 ◽  
Author(s):  
P. J. Jasinski ◽  
H.-P. Meinzer ◽  
C. O. Köhler ◽  
B. Sandblad
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
Digital Images ◽  
Image Data ◽  
Data Type ◽  
Medical Applications ◽  
Basic Notion ◽  
Heterogeneous Information ◽  
Database Technology

SummaryThe structure of computer-processed images is described. This is the basis for presenting a method to integrate traditional database concepts and images which represent a certain class of nonformatted, heterogeneous information. The method presented consists of a special, surrogate Image data type and a design of Image Directory, which associates formatted data, raw digital images stored conceptually in the form of a file of variable length, bit string records, and look-up tables. Beside individual and aggregate-oriented retrieval, some tools supporting more sophisticated analyses of images are also suggested. In order to make the description of solutions clear and truly methodological, a basic notion of the relational database technology and a de facto standard query language (SQL) have been applied. The method presented can be used to build various medical applications where images and/or graphics constitute an important fraction of information.

scholarly journals Storage organization for "open" sets of entity attributes in relational databases

2021 ◽  
Vol 12 (5-2021) ◽  
pp. 128-139
Author(s):  
Andrey G. Oleynik ◽  
Keyword(s):  
Information Systems ◽  
Relational Database ◽  
Database Management ◽  
Relational Databases ◽  
Database Management Systems ◽  
Management Systems ◽  
Two Dimensional ◽  
Open Set ◽  
Special Relations

Relations are practically implemented by database management systems in the form of two-dimensional tables. In this regard, certain difficulties arise in the development of relational database schemas, in which it is necessary to represent objects with an alterable (open) set of attributes. The article proposes a solution to this problem by including special relations in the scheme - relations of properties directory. Properties directory allow replenishing the sets of object attributes without changing the structure of the database. Examples of the practical use of properties directory in the development of database schemas of two information systems are presented.

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