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A method to evaluate database management systems for Big Data: focus on spatial data
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Big data of type spatial is growing exponentially with the highest rate due to extensive growth in usage of sensors, IoT and mobile devices’ spatial data generation, therefore maintaining, processing and using such data efficiently, effectively with high performance has become one of the top priorities for Database management system providers, hence spatial database features and datatypes have become serious criteria in evaluating database management systems that are supposed to work as the back-end for spatial applications and services.

With exponential growth of data and introducing of new types of data, “Big Data” has become strongly focused area that has gained the attention of different sectors e.g. academia, industries and governments to other organizations and studies.

The rising trend in high resolution and large-scale geographical information systems have resulted in more companies providing location-based applications and services, therefore finding a proper database management system solution that can support spatial big data features, with multi-model big data support that is reliable and affordable has become a business need for many companies.

Concerning the fact that choosing proper solution for any software project can be crucial due to the total cost and desired functionalities that any product could possibly bring into the solution. Migration is also a very complicated and costly procedure that many companies should avoid, which justifies the criticality of choosing the right solution based on the specific needs of any organization.

Companies providing spatial applications and services are growing with the common concern of providing successful solutions and robust services. One of the most significant elements that ensures services’ and hence the providers’ reputation and positive depiction is services’ high availability.

The possible future work for the thesis could be to develop the framework into a decision support solution for IT businesses with emphasize on spatial features. Another possibility for the future works would be to evaluate the framework by testing the evaluation framework on many other different DBMSs.

Place, publisher, year, edition, pages
2019. , p. 63
Keywords [en]
Big Data, spatial database, DBMS, GIS, selection method
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:ltu:diva-74172OAI: oai:DiVA.org:ltu-74172DiVA, id: diva2:1320171
External cooperation
Mobilaris AB.
Subject / course
Student thesis, at least 30 credits
Educational program
Information Security, master's level (120 credits)
Supervisors
Examiners
Available from: 2019-06-05 Created: 2019-06-04 Last updated: 2019-06-05Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • Other locale
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Output format
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