scholarly journals Comparison of object-relational data mapping technology in Symfony 3 framework

2018 ◽  
Vol 8 ◽  
pp. 235-240
Author(s):  
Karol Sawłuk ◽  
Marek Miłosz
Keyword(s):  
Comparative Analysis ◽  
Object Relation ◽  
Efficient Algorithms ◽  
Relational Data ◽  
Data Mapping ◽  
Memory Usage ◽  
Object Relational ◽  
Mapping Technology ◽  
Execution Speed ◽  
Database Operations

The article presents the results of a comparative analysis of object-relation mapping technologies in the framework Symfony 3: Doctrine and Propel. The analysis was performed in terms of script execution speed and memory usage during database operations. The analysis allowed to identify the technology with faster and more efficient algorithms. Doctrine is up to three times faster than Propel.

Data Mining on XML Data

2011 ◽  
pp. 506-510
Author(s):  
Qin Ding
Keyword(s):  
Data Mining ◽  
Data Storage ◽  
Efficient Algorithms ◽  
Relational Data ◽  
Xml Data ◽  
Structure Information ◽  
Data Mining Algorithms ◽  
Mining Algorithms ◽  
Naive Approach

With the growing usage of XML data for data storage and exchange, there is an imminent need to develop efficient algorithms to perform data mining on semistructured XML data. Mining on XML data is much more difficult than mining on relational data because of the complexity of structure in XML data. A naïve approach to mining on XML data is to first convert XML data into relational format. However the structure information may be lost during the conversion. It is desired to develop efficient and effective data mining algorithms that can be directly applied on XML data.

Efficient Query Processing with Structural Join Indexing in an Object Relational Data Warehousing Environment

2011 ◽  
pp. 243-256
Author(s):  
Vivekanand Gopalkrishnan ◽  
Qing Li ◽  
Kamalakar Karlapalem
Keyword(s):  
Query Processing ◽  
Data Warehousing ◽  
Cost Model ◽  
Hill Climbing ◽  
Relational Data ◽  
Structural Join ◽  
Object Relational ◽  
Hybrid Data ◽  
Efficient Query Processing ◽  
Query Semantics

In an Object Relational Data Warehousing (ORDW) environment, the semantics of data and queries can be explicitly captured, represented, and utilized based on is-a and class composition hierarchies, thereby resulting in more efficient OLAP query processing. In this chapter, we show the efficacy in building semantic-rich hybrid data indexes incorporating Structural Join Index Hierarchy (SJIH) on the ORDW views. Given a set of queries, we use a hill-climbing heuristic algorithm to select (near) optimal SJIHs, thereby embedding query semantics into the indexing framework. Finally, by a cost model, we analyze the effectiveness of our approach vis-a-vis the pointer chasing approach.

scholarly journals When Relational-Based Applications Go to NoSQL Databases: A Survey

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 241
Author(s):  
Geomar A. Schreiner ◽  
Denio Duarte ◽  
Ronaldo dos S. Melo
Keyword(s):  
Big Data ◽  
Comparative Analysis ◽  
Relational Databases ◽  
Research Area ◽  
Relational Data ◽  
Data Sets ◽  
System Architectures ◽  
Nosql Databases ◽  
State Of Art ◽  
Open Issues

Several data-centric applications today produce and manipulate a large volume of data, the so-called Big Data. Traditional databases, in particular, relational databases, are not suitable for Big Data management. As a consequence, some approaches that allow the definition and manipulation of large relational data sets stored in NoSQL databases through an SQL interface have been proposed, focusing on scalability and availability. This paper presents a comparative analysis of these approaches based on an architectural classification that organizes them according to their system architectures. Our motivation is that wrapping is a relevant strategy for relational-based applications that intend to move relational data to NoSQL databases (usually maintained in the cloud). We also claim that this research area has some open issues, given that most approaches deal with only a subset of SQL operations or give support to specific target NoSQL databases. Our intention with this survey is, therefore, to contribute to the state-of-art in this research area and also provide a basis for choosing or even designing a relational-to-NoSQL data wrapping solution.

scholarly journals Comparative analysis of selected object-relational mapping systems for the .NET platform

2020 ◽  
Vol 16 ◽  
pp. 285-292
Author(s):  
Krzysztof Drzazga ◽  
Marcin Bobel ◽  
Maria Skublewska-Paszkowska
Keyword(s):  
Comparative Analysis ◽  
Efficiency Analysis ◽  
Research Hypothesis ◽  
Desktop Application ◽  
Relational Mapping ◽  
Object Relational ◽  
The Stability ◽  
Mapping Systems

This article is devoted to the comparison of two object-relational mapping systems supported by .NET platform - Entity Framework Core and NHibernate. The research hypothesis “framework NHibernate is more efficient than Entity Framework Core in the context of DML operations” was put forward. In order to make an efficiency analysis of ORM frameworks, a desktop application was designed and implemented to enable testing and visualization of results. The NHibernate framework turned out to be much more efficient than Entity Framework Core in single tests and slightly faster in bulk tests. The stability of both frameworks was similar.

scholarly journals The Application of Management System ORDBMS Object Relational Data Base in System by Using ORACCL

2005 ◽  
Vol 27 (80) ◽  
pp. 23-38
Author(s):  
Isam M. Mohammed ◽  
Asma Y. Hamo ◽  
Alaa F. saeed
Keyword(s):  
Data Base ◽  
Management System ◽  
Relational Data ◽  
Object Relational ◽  
Relational Data Base

scholarly journals Comparative analysis of a selected version of the Symfony framework

2020 ◽  
Vol 15 ◽  
pp. 178-183
Author(s):  
Michał Jusięga ◽  
Mariusz Dzieńkowski
Keyword(s):  
Comparative Analysis ◽  
Basic Component ◽  
Performance Tests ◽  
Memory Usage ◽  
Simple Test ◽  
Two Stage ◽  
Programming Framework ◽  
Code Fragment ◽  
Test Application ◽  
Quantitative Analyses

This article is about research during which selected versions of the Symfony programming framework were compared in terms of their performance. The following versions of the framework were analysed: 3.0, 3.1, 3.2, 3.3, 3.4 LTS, 4.0, 4.1, 4.2, 4.3 and 4.4 LTS. For the purpose of the research, a simple test application in PHP was developed in ten variants corresponding to selected versions of the framework and consisting of 17 fragments of code – methods in the class, each of which operates on one basic component of Symfony. The application prepared in this manner was subject to performance tests in a two-stage experiment. After the experiment, the quantitative analyses were conducted in which the following aspects were taken into consideration: the average values of execution times and the average amounts of memory usage for specific code fragments for individual versions of the Symfony framework components and the average time of execution and demand for memory for the entire tested application. The obtained results for each code fragment representing a given component were visualized in the forms of graphs. The performed analyses showed that the best version of the Symfony programming framework in terms of performance is version 4.1.

scholarly journals Semantic data mapping technology to solve semantic data problem on heterogeneity aspect

2017 ◽  
Vol 3 (3) ◽  
pp. 161 ◽  
Author(s):  
Arda Yunianta ◽  
Omar Mohammed Barukab ◽  
Norazah Yusof ◽  
Nataniel Dengen ◽  
Haviluddin Haviluddin ◽  
...  
Keyword(s):  
Real Data ◽  
Database Systems ◽  
Data Mapping ◽  
Semantic Data ◽  
Ontology Language ◽  
Data Problem ◽  
Mapping Technology ◽  
Application Data ◽  
Semantic Aspect ◽  
Mapping File

The diversity of applications developed with different programming languages, application/data architectures, database systems and representation of data/information leads to heterogeneity issues. One of the problem challenges in the problem of heterogeneity is about heterogeneity data in term of semantic aspect. The semantic aspect is about data that has the same name with different meaning or data that has a different name with the same meaning. The semantic data mapping process is the best solution in the current days to solve semantic data problem. There are many semantic data mapping technologies that have been used in recent years. This research aims to compare and analyze existing semantic data mapping technology using five criteria’s. After comparative and analytical process, this research provides recommendations of appropriate semantic data mapping technology based on several criteria’s. Furthermore, at the end of this research we apply the recommended semantic data mapping technology to be implemented with the real data in the specific application. The result of this research is the semantic data mapping file that contains all data structures in the application data source. This semantic data mapping file can be used to map, share and integrate with other semantic data mapping from other applications and can also be used to integrate with the ontology language.

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