Mobile Data Store Platforms: Test Case based Performance Evaluation

2016

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DOI 10.5220/0006032300950099
Data confidence 70 medium
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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.