A Comparative Analysis of Materialized Views Selection and Concurrency Control Mechanisms in NoSQL Databases
Ashish Tapdiya, Yuan Xue, Daniel Fabbri (Vanderbilt University)

TL;DR
This paper introduces Synergy, a system that enhances NoSQL databases with materialized views and specialized concurrency control to improve join performance and query expressiveness while maintaining ACID properties.
Contribution
It proposes a schema and workload driven approach to select materialized views and concurrency control mechanisms, balancing performance, disk utilization, and query expressiveness in NoSQL databases.
Findings
Achieves up to 80.5% performance improvement on TPC-W benchmark.
Improves join performance over standard NoSQL databases.
Balances ACID semantics with scalable data management.
Abstract
Increasing resource demands require relational databases to scale. While relational databases are well suited for vertical scaling, specialized hardware can be expensive. Conversely, emerging NewSQL and NoSQL data stores are designed to scale horizontally. NewSQL databases provide ACID transaction support; however, joins are limited to the partition keys, resulting in restricted query expressiveness. On the other hand, NoSQL databases are designed to scale out linearly on commodity hardware; however, they are limited by slow join performance. Hence, we consider if the NoSQL join performance can be improved while ensuring ACID semantics and without drastically sacrificing write performance, disk utilization and query expressiveness. This paper presents the Synergy system that leverages schema and workload driven mechanism to identify materialized views and a specialized concurrency…
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