The Time Machine in Columnar NoSQL Databases: The Case of Apache HBase

Chia-Ping Tsai, Che-Wei Chang, Hung-Chang Hsiao and Haiying Shen
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Chia-Ping Tsai: Apache HBase and Kafka Project Management Committees, Wilmington, DE 19801, USA
Che-Wei Chang: Department of Computer Science and Information Engineering, Chinese Culture University, Taipei 11114, Taiwan
Hung-Chang Hsiao: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 70101, Taiwan
Haiying Shen: Department of Computer Science, University of Virginia, Charlottesville, VA 22908, USA

Future Internet, 2022, vol. 14, issue 3, 1-20

Abstract: Not Only SQL (NoSQL) is a critical technology that is scalable and provides flexible schemas, thereby complementing existing relational database technologies. Although NoSQL is flourishing, present solutions lack the features required by enterprises for critical missions. In this paper, we explore solutions to the data recovery issue in NoSQL. Data recovery for any database table entails restoring the table to a prior state or replaying (insert/update) operations over the table given a time period in the past. Recovery of NoSQL database tables enables applications such as failure recovery, analysis for historical data, debugging, and auditing. Particularly, our study focuses on columnar NoSQL databases. We propose and evaluate two solutions to address the data recovery problem in columnar NoSQL and implement our solutions based on Apache HBase, a popular NoSQL database in the Hadoop ecosystem widely adopted across industries. Our implementations are extensively benchmarked with an industrial NoSQL benchmark under real environments.

Keywords: NoSQL; backup; recovery; Hadoop; HBase; MapReduce; big data (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
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