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Authors: Karim Kussainov and Bolatzhan Kumalakov

Affiliation: Nazarbayev University, Kazakhstan

Keyword(s): Mobile Database, SQLite, Realm, SnappyDB, Performance Evaluation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Symbolic Systems ; Tools and Technology for Knowledge Management

Abstract: Mobile applications are an important tool in knowledge management, as they collect and process massive amount of user data. Day-to-day usage of mobile services has rocketed by factors over the last decade. Average mobile device user installs multiple social network, messaging, professional and leisure applications. Saving and retrieving associated data becomes a challenging task in the light of the growing number of applications on a single device. While industry offers several well established platforms, such as BerkeleyDB and UnQLite, we examine comparatively poorly examined Realm and SnappyDB against industry standard - SQLite. In particular we are interested in performance and code maintainability, and use a test case in order to asses them. Results revile that SQLite shows the poorest performance, while Realm provides the most intuitive way of matching data to the application logic due to its object-oriented nature.

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Paper citation in several formats:
Kussainov, K. and Kumalakov, B. (2016). Mobile Data Store Platforms: Test Case based Performance Evaluation. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KMIS; ISBN 978-989-758-203-5; ISSN 2184-3228, SciTePress, pages 95-99. DOI: 10.5220/0006032300950099

@conference{kmis16,
author={Karim Kussainov. and Bolatzhan Kumalakov.},
title={Mobile Data Store Platforms: Test Case based Performance Evaluation},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KMIS},
year={2016},
pages={95-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006032300950099},
isbn={978-989-758-203-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KMIS
TI - Mobile Data Store Platforms: Test Case based Performance Evaluation
SN - 978-989-758-203-5
IS - 2184-3228
AU - Kussainov, K.
AU - Kumalakov, B.
PY - 2016
SP - 95
EP - 99
DO - 10.5220/0006032300950099
PB - SciTePress