scholarly journals Managing the Data Effectively Using Object Relational Data Store

2017 ◽  
Vol 6 (7) ◽  
pp. 669-673
Keyword(s):  
Relational Data ◽  
Data Store ◽  
Object Relational

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 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.

scholarly journals Comparing speed of Web Map Service with GeoServer on ESRI Shapefile and PostGIS

2016 ◽  
Vol 15 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Jan Růžička
Keyword(s):  
Relational Database ◽  
Data Sources ◽  
Advantages And Disadvantages ◽  
Web Map ◽  
Data Store ◽  
Object Relational ◽  
Data Source ◽  
Map Service

There are several options how to configure Web Map Service using several map servers. GeoServer is one of most popular map servers nowadays. GeoServer is able to read data from several sources. Very popular data source is ESRI Shapefile. It is well documented and most of software for geodata processing is able to read and write data in this format. Another very popular data store is PostgreSQL/PostGIS object-relational database. Both data sources has advantages and disadvantages and user of GeoServer has to decide which one to use. The paper describes comparison of performance of GeoServer Web Map Service when reading data from ESRI Shapefile or from PostgreSQL/PostGIS database.

scholarly journals Model-based exception mining for object-relational data

2020 ◽  
Vol 34 (3) ◽  
pp. 681-722 ◽  
Author(s):  
Fatemeh Riahi ◽  
Oliver Schulte
Keyword(s):  
Relational Data ◽  
Model Based ◽  
Object Relational
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