Computer Science
Practical Experience Report: Cassandra+: Trading-Off Consistency, Latency, and Fault-tolerance in Cassandra
Document Type
Conference Paper
Abstract
The exponential growth of data has pushed the industry towards new types of data management systems such as NoSQL database. Our goal is to augment NoSQL, with the focus on its application as a distributed key-value store (KV-store). Existing production-ready systems often provide only probabilistic guarantees on consistency and fault-tolerance, and may violate their correctness properties if a cluster has severe clock drift. Our system Cassandra+ addresses these issues by providing more choices for consistency and fault-tolerance. We build Cassandra+ by implementing theoretical distributed shared memory (DSM) in Cassandra, one of the most popular NoSQLs in the industry. In this paper, we share our experience in adapting and implementing DSM algorithms into a real-world system. We hope our experience and results allow a better understanding of the DSM and the tradeoffs involved.
Publication Title
ACM International Conference Proceeding Series
Publication Date
2021
First Page
191
Last Page
195
ISBN
9781450389334
DOI
10.1145/3427796.3427816
Keywords
Cassandra, consistency, distributed KV-store, evaluation, fault-tolerance, implementation
Repository Citation
Gao, Guo Shu; Konwar, Kishori; Mantica, Juan; Pan, Haochen; Russell Kish, Darius; Tseng, Lewis; Wang, Zezhi; and Wu, Yingjian, "Practical Experience Report: Cassandra+: Trading-Off Consistency, Latency, and Fault-tolerance in Cassandra" (2021). Computer Science. 112.
https://commons.clarku.edu/faculty_computer_sciences/112
APA Citation
Gao, G. S., Konwar, K., Mantica, J., Pan, H., Russell Kish, D., Tseng, L., ... & Wu, Y. (2021, January). Practical Experience Report: Cassandra+: Trading-Off Consistency, Latency, and Fault-tolerance in Cassandra. In Proceedings of the 22nd International Conference on Distributed Computing and Networking (pp. 191-195).
