scholarly journals Using a DBMS based on various data models in solving problems of cartography and geoinformatics

2021 ◽  
Vol 310 ◽  
pp. 06001
Author(s):  
Alexey A. Kolesnikov ◽  
Pavel M. Kikin
Keyword(s):  
Comparative Analysis ◽  
Spatial Data ◽  
Database Management ◽  
Database Management Systems ◽  
Data Models ◽  
Management Systems ◽  
Spatial Queries ◽  
Vector Data ◽  
Novosibirsk Region

An increasing number of database management systems are expanding their functionality to work with various types of spatial data. This is true for both relational and NoSQL data models. The article describes the main features of those data models for which the functions of storing and processing spatial data are implemented. A comparative analysis of the performance of typical spatial queries for database management systems based on various data models, including multi-model ones, is carried out. The dataset on which the comparison is performed is presented in the form of three blocks of OpenStreetMap vector data for the territory of the Novosibirsk region. Based on the results of the study, recommendations are made on the use of certain data models, depending on the available data and the tasks to be solved.

scholarly journals Comparative analysis of databases working under the control of Windows system

2019 ◽  
Vol 13 ◽  
pp. 298-301
Author(s):  
Serhii Stets ◽  
Grzegorz Kozieł
Keyword(s):  
Comparative Analysis ◽  
Database Management ◽  
Database Management Systems ◽  
Management Systems ◽  
Query Performance ◽  
Second Stage ◽  
The Third ◽  
Third Stage ◽  
Analysis Of Results

The aim of this paper is to conduct research on the most popular database management systems such as MySQL, PostgreSQL and Firebird in terms of query performance, CPU load and disk usage. At the first stage, the analysis of the popularity of databases was carried out. In the second stage an application was created that allows for communication with selected databases. At the third stage, tests were carried out using a written application and analysis of results.

Integrity Issues in the Web

2002 ◽  
pp. 293-321 ◽  
Author(s):  
Jose F. Aladana Montes ◽  
Mariemma I. Yague del Valle ◽  
Antonio C. Gomez Lora
Keyword(s):  
Database Management ◽  
Relational Databases ◽  
Distributed Databases ◽  
Database Management Systems ◽  
Data Models ◽  
Management Systems ◽  
New Paradigm ◽  
File Management ◽  
Object Relational ◽  
The Web

Issues related to integrity in databases and distributed databases have been introduced in previous chapters. Therefore, the integrity problem in databases and how it can be managed in several data models (relational, active, temporal, geographical, and object-relational databases) are well known to the reader. The focus of this chapter is on introducing a new paradigm: The Web as the database, and its implications regarding integrity, i.e., the progressive adaptation of database techniques to Web usage. We consider that this will be done in a quite similar way to the evolution from integrated file management systems to database management systems.

Riso-Tree: An Efficient and Scalable Index for Spatial Entities in Graph Database Management Systems

2021 ◽  
Vol 7 (3) ◽  
pp. 1-39
Author(s):  
Yuhan Sun ◽  
Mohamed Sarwat
Keyword(s):  
Spatial Data ◽  
Database Management ◽  
Spatial Location ◽  
Database Management Systems ◽  
Management Systems ◽  
Graph Database ◽  
Index Maintenance ◽  
Spatial Attributes ◽  
Graph Queries ◽  
Spatial Entities

With the ubiquity of spatial data, vertexes or edges in graphs can possess spatial location attributes side by side with other non-spatial attributes. For instance, as of June 2018, the Wikidata knowledge graph contains 48,547,142 data items (i.e., vertexes) and 13% of them have spatial location attributes. The article proposes Riso-Tree, a generic efficient and scalable indexing framework for spatial entities in graph database management systems. Riso-Tree enables the fast execution of graph queries that involve different types of spatial predicates (GraSp queries). The proposed framework augments the classic R-Tree structure with pre-materialized sub-graph entries. The pruning power of R-Tree is enhanced with the sub-graph information. Riso-Tree partitions the graph into sub-graphs based on their connectivity to the spatial sub-regions. The proposed index allows for the fast execution of GraSp queries by efficiently pruning the traversed vertexes/edges based upon the materialized sub-graph information. The experiments show that the proposed Riso-Tree achieves up to two orders of magnitude faster execution time than its counterparts when executing GraSp queries on real graphs (e.g., Wikidata). The strategy of limiting the size of each sub-graph entry ( PN max ) is proposed to reduce the storage overhead of Riso-Tree. The strategy can save up to around 70% storage without harming the query performance according to the experiments. Another strategy is proposed to ensure the performance of the index maintenance (Irrelevant Vertexes Skipping). The experiments show that the strategy can improve performance, especially for slow updates. It proves that Riso-Tree is useful for applications that need to support frequent updates.

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