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NoSQL Databases in the Enterprise. An Experience with Tomra s Receipt Validation System

Dzhakishev, Davlet
Master thesis
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Dzhakishev---Master.pdf (8.160Mb)
Year
2014
Permanent link
http://urn.nb.no/URN:NBN:no-46637

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  • Institutt for informatikk [3608]
Abstract
The information processing demands of many of today's businesses have outgrown the legacy relational database management system (RDBMS) software resulting from both the data explosive growth and the variety of data models. Today, businesses must manage increasingly large volumes of data that must be available across distributed systems and as well as able to evolve and adapt data models according to the changes of business requirements. Enterprises across all industries are challenged by the task of ensuring scalability of massive quantities of data while at the same time keeping database models simple and flexible at the same time. A new and advanced set of software, "NoSQL" as it is so called, has emerged in response to this challenge and offer new methods for storing data. The NoSQL ecosystem has flourished, with numerous software contributions appearing under the NoSQL umbrella. However, as more enterprises have implemented NoSQL solutions, a distinctive set of criteria has emerged that can help today's IT professionals more easily make use of NoSQL solutions built for enterprise-wide development. In this thesis we investigate the usage of NoSQL solutions in the enterprise environment, where RDBMS traditionally run the show. Tomra AS provided us with the industrial case, featuring implementation of the distributed system for validation of receipts, using two different NoSQL databases. In this work, we describe implementation of the receipt validation system and evaluate NoSQL solutions, based on variety of criteria, such as performance, scalability and ease of use. We also describe the advantages NoSQL approach has over SQL (RDBMS) approaches in a distributed environment. The goal is to help decision makers in the enterprise to make better informed judgements when choosing a particular set of database software for their data handling strategies.
 
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