scholarly journals A Simpler and Semantic Multidimensional Database Query Language to Facilitate Access to Information in Decision-making

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Fredi Edgardo Palominos ◽  
Felisa Córdova ◽  
Claudia Durán ◽  
Bryan Nuñez
Keyword(s):  
Decision Making ◽  
Query Language ◽  
Database Systems ◽  
Relational Algebra ◽  
Multidimensional Database ◽  
Management Indicators ◽  
Relational Calculus ◽  
Database Technology ◽  
Sql Language ◽  
Relational Database Systems

OLAP and multidimensional database technology have contributed significantly to speed up and build confidence in the effectiveness of methodologies based on the use of management indicators in decision-making, industry, production, and services. Although there are a wide variety of tools related to the OLAP approach, many implementations are performed in relational database systems (R-OLAP). So, all interrogation actions are performed through queries that must be reinterpreted in the SQL language. This translation has several consequences because SQL language is based on a mixture of relational algebra and tuple relational calculus, which conceptually responds to the logic of the relational data model, very different from the needs of the multidimensional databases. This paper presents a multidimensional query language that allows expressing multidimensional queries directly over ROLAP databases. The implementation of the multidimensional query language will be done through a middleware that is responsible for mapping the queries, hiding the translation to a layer of software not noticeable to the end-user. Currently, progress has been made in the definition of a language where through a key statement, called aggregate, it is possible to execute the typical multidimensional operators which represent an important part of the most frequent operations in this type of database.

scholarly journals Array databases: concepts, standards, implementations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peter Baumann ◽  
Dimitar Misev ◽  
Vlad Merticariu ◽  
Bang Pham Huu
Keyword(s):  
Service Quality ◽  
Ad Hoc ◽  
Query Language ◽  
Distributed Processing ◽  
Database Systems ◽  
Database Technology ◽  
Comprehensive Survey ◽  
Spatio Temporal ◽  
And Performance ◽  
Array Databases

AbstractMulti-dimensional arrays (also known as raster data or gridded data) play a key role in many, if not all science and engineering domains where they typically represent spatio-temporal sensor, image, simulation output, or statistics “datacubes”. As classic database technology does not support arrays adequately, such data today are maintained mostly in silo solutions, with architectures that tend to erode and not keep up with the increasing requirements on performance and service quality. Array Database systems attempt to close this gap by providing declarative query support for flexible ad-hoc analytics on large n-D arrays, similar to what SQL offers on set-oriented data, XQuery on hierarchical data, and SPARQL and CIPHER on graph data. Today, Petascale Array Database installations exist, employing massive parallelism and distributed processing. Hence, questions arise about technology and standards available, usability, and overall maturity. Several papers have compared models and formalisms, and benchmarks have been undertaken as well, typically comparing two systems against each other. While each of these represent valuable research to the best of our knowledge there is no comprehensive survey combining model, query language, architecture, and practical usability, and performance aspects. The size of this comparison differentiates our study as well with 19 systems compared, four benchmarked to an extent and depth clearly exceeding previous papers in the field; for example, subsetting tests were designed in a way that systems cannot be tuned to specifically these queries. It is hoped that this gives a representative overview to all who want to immerse into the field as well as a clear guidance to those who need to choose the best suited datacube tool for their application. This article presents results of the Research Data Alliance (RDA) Array Database Assessment Working Group (ADA:WG), a subgroup of the Big Data Interest Group. It has elicited the state of the art in Array Databases, technically supported by IEEE GRSS and CODATA Germany, to answer the question: how can data scientists and engineers benefit from Array Database technology? As it turns out, Array Databases can offer significant advantages in terms of flexibility, functionality, extensibility, as well as performance and scalability—in total, the database approach of offering “datacubes” analysis-ready heralds a new level of service quality. Investigation shows that there is a lively ecosystem of technology with increasing uptake, and proven array analytics standards are in place. Consequently, such approaches have to be considered a serious option for datacube services in science, engineering and beyond. Tools, though, vary greatly in functionality and performance as it turns out.

scholarly journals Analysis of the possibilities of optimizing SQL queries

2021 ◽  
Vol 19 ◽  
pp. 151-158
Author(s):  
Piotr Rymarski ◽  
Grzegorz Kozieł
Keyword(s):  
Relational Database ◽  
Web Applications ◽  
Query Language ◽  
Database Systems ◽  
Sql Server ◽  
Management Systems ◽  
Relational Database Systems ◽  
The Impact ◽  
Relational Database Management ◽  
Test Scenarios

Most of today's web applications run on relational database systems. Communication with them is possible through statements written in Structured Query Language (SQL). This paper presents the most popular relational database management systems and describes common ways to optimize SQL queries. Using the research environment based on fragment of the imdb.com database, implementing OracleDb, MySQL, Microsoft SQL Server and PostgreSQL engines, a number of test scenarios were performed. The aim was to check the performance changes of SQL queries resulting from syntax modication while maintaining the result, the impact of database organization, indexing and advanced mechanisms aimed at increasing the eciency of operations performed, delivered in the systems used. The tests were carried out using a proprietary application written in Java using the Hibernate framework.

Fuzzy Classification on Relational Databases

2011 ◽  
pp. 586-614 ◽  
Author(s):  
Andreas Meier ◽  
Günter Schindler ◽  
Nicolas Werro
Keyword(s):  
Relational Databases ◽  
Information Overload ◽  
Query Language ◽  
Large Data ◽  
Database Systems ◽  
Fuzzy Classification ◽  
Linguistic Variables ◽  
Context Model ◽  
Relational Database Systems ◽  
Data Collections

In practice, information systems are based on very large data collections mostly stored in relational databases. As a result of information overload, it has become increasingly difficult to analyze huge amounts of data and to generate appropriate management decisions. Furthermore, data are often imprecise because they do not accurately represent the world or because they are themselves imperfect. For these reasons, a context model with fuzzy classes is proposed to extend relational database systems. More precisely, fuzzy classes and linguistic variables and terms, together with appropriate membership functions, are added to the database schema. The fuzzy classification query language (fCQL) allows the user to formulate unsharp queries that are then transformed into appropriate SQL statements using the fCQL toolkit so that no migration of the raw data is needed. In addition to the context model with fuzzy classes, fCQL and its implementation are presented here, illustrated by concrete examples.

A Universal Relation Approach For Natural Query In Logic Database System

1992 ◽  
pp. 46-64
Author(s):  
Harihodin Selamat
Keyword(s):  
Query Language ◽  
Database Systems ◽  
Optimization Techniques ◽  
Deductive Database ◽  
Universal Relation ◽  
Data Types ◽  
Natural Language Query ◽  
Query System ◽  
Relational Database Systems ◽  
Relation Approach

Recent advances in Artificial Intelligence and Relational Database systems have contributed to the development of Logic Database systems. A lot of research in logic database have been encompassed on the query evaluation and optimization techniques. Very litde effort has been put to the development of the user's query system to facilitate the naive users interacting with the database. Currently, the form of query is based on the primitive logic form. Therefore, this project aims at developing a prototype natural query system to the logic database as a compromise between the primitive logic query and the natural language query systems. This paper describes a conceptual framework of the natural query system. The concept of predicate universal relation is introduced as an interface to bridge the natural query and the corresponding primitive logic query. The concept of data types is employed as a tool towards the construction of the predicate universal relation. We believe this is the first attempt towards a natural query system for logic database via a universal relation approach. Keywords: query interface, logic database, deductive database, universal relation, query processing, query language, natural query, first order logic, data types

Access path query language for relational database systems

1983 ◽  
Vol 13 (8) ◽  
pp. 661-670
Author(s):  
L. M. Patnaik ◽  
Phule Shailendra ◽  
K. Venkateswara Rao
Keyword(s):  
Relational Database ◽  
Query Language ◽  
Database Systems ◽  
Access Path ◽  
Relational Database Systems

Towards the Maturity of Object-Relational Database Technology: Promises and Reality

2015 ◽  
Vol 6 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Negin Keivani ◽  
Abdelsalam M. Maatuk ◽  
Shadi Aljawarneh ◽  
Muhammad Akhtar Ali
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Database Systems ◽  
Database System ◽  
Relational Database System ◽  
Key Factor ◽  
Object Relational ◽  
Database Technology ◽  
Relational Database Systems ◽  
Additional Object

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 the performance implications of using object-relational relative to relational technology, the query-oriented BUCKY benchmark has been previously applied to an early object-relational database system, i.e., Illustra 97. This paper presents the results obtained from implementing and running the BUCKY benchmark on Oracle 10g. The results acquired from the work described in this paper are compared with the results obtained in BUCKY benchmark. This study throws light on the functionality of object-relational databases, where object-relational technology has made improvements but some limitations are identified as well. In general, the performance of relational supersedes that of object-relational database system.

Computer Technologies in Logic Education

2011 ◽  
pp. 144-149
Author(s):  
Yefim Kats
Keyword(s):  
Information Technology ◽  
Educational Software ◽  
Query Language ◽  
Database Systems ◽  
Sql Server ◽  
College Level ◽  
Microsoft Access ◽  
Software Packages ◽  
Relational Calculus ◽  
Industrial Software

The recent truly revolutionary changes in information technology triggered the rapid proliferation of educational software supporting introductory as well as advanced college-level logic courses. At the same time, many commercial software packages represent a more or less explicit implementation of logic-based programming paradigm. For example, sequential query language (SQL), designed for such popular database management products as Microsoft Access, Microsoft SQL Server, Oracle, and free- source MySQL, is based on logical query language called relational calculus. From this perspective, it seems not only desirable, but also imperative to introduce carefully selected industrial software packages into the standard Logic and Critical Thinking courses, thus, explicitly linking logical theory with existing as well as emerging applications in information technology. Some of such applications would include database systems, data mining, logic programming, and Web ontologies, among others. Artificial intelligence is still another multidisciplinary area where logic plays an especially prominent role. In this paper, we intend to show how logic-based industrial software can be used in conjunction with specialized as well as broad-based logic courses.

Database Queries, Data Mining, and OLAP

2011 ◽  
pp. 598-603
Author(s):  
Lutz Hamel
Keyword(s):  
Data Mining ◽  
Relational Database ◽  
Query Language ◽  
Data Retrieval ◽  
Database Systems ◽  
Database Queries ◽  
On Line ◽  
Analytical Processing ◽  
Relational Database Systems ◽  
Complementary Value

Modern, commercially available relational database systems now routinely include a cadre of data retrieval and analysis tools. Here we shed some light on the interrelationships between the most common tools and components included in today’s database systems: query language engines, data mining components, and on-line analytical processing (OLAP) tools. We do so by pair-wise juxtaposition which will underscore their differences and highlight their complementary value.

Database Queries, Data Mining, and OLAP

2011 ◽  
pp. 339-343
Author(s):  
Lutz Hamel
Keyword(s):  
Data Mining ◽  
Relational Database ◽  
Query Language ◽  
Data Retrieval ◽  
Database Systems ◽  
Database Queries ◽  
Analytical Processing ◽  
Relational Database Systems ◽  
Complementary Value ◽  
Do So

Modern, commercially available relational database systems now routinely include a cadre of data retrieval and analysis tools. Here we shed some light on the interrelationships between the most common tools and components included in today’s database systems: query language engines, data mining components, and online analytical processing (OLAP) tools. We do so by pair-wise juxtaposition, which will underscore their differences and highlight their complementary value.

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