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Constructing a Lightweight Key-Value Store Based on the Windows Native Features

Department of Industrial and Systems Engineering and the Research Center for Electrical and Information Technology, Seoul National University of Science and Technology, 232 Gongneung-Ro, Nowon-Gu, Seoul 01811, Korea
Appl. Sci. 2019, 9(18), 3801; https://doi.org/10.3390/app9183801
Received: 22 August 2019 / Revised: 5 September 2019 / Accepted: 7 September 2019 / Published: 11 September 2019
(This article belongs to the Section Computing and Artificial Intelligence)
In this paper, we propose a method to construct a lightweight key-value store based on the Windows native features. The main idea is providing a thin wrapper for the key-value store on top of a built-in storage in Windows, called Windows registry. First, we define a mapping of the components in the key-value store onto the components in the Windows registry. Then, we present a hash-based multi-level registry index so as to distribute the key-value data balanced and to efficiently access them. Third, we implement basic operations of the key-value store (i.e., Get, Put, and Delete) by manipulating the Windows registry using the Windows native APIs. We call the proposed key-value store WR-Store. Finally, we propose an efficient ETL (Extract-Transform-Load) method to migrate data stored in WR-Store into any other environments that support existing key-value stores. Because the performance of the Windows registry has not been studied much, we perform the empirical study to understand the characteristics of WR-Store, and then, tune the performance of WR-Store to find the best parameter setting. Through extensive experiments using synthetic and real data sets, we show that the performance of WR-Store is comparable to or even better than the state-of-the-art systems (i.e., RocksDB, BerkeleyDB, and LevelDB). Especially, we show the scalability of WR-Store. That is, WR-Store becomes much more efficient than the other key-value stores as the size of data set increases. In addition, we show that the performance of WR-Store is maintained even in the case of intensive registry workloads where 1000 processes accessing to the registry actively are concurrently running. View Full-Text
Keywords: databases; data stores; key-value stores; performance evaluation databases; data stores; key-value stores; performance evaluation
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Kwon, H.-Y. Constructing a Lightweight Key-Value Store Based on the Windows Native Features. Appl. Sci. 2019, 9, 3801.

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