Source :
2017 IEEE International Conference on Cluster Computing
Descriptors :
Transaction processing , materialized views , NoSQL databases , performance evaluation
Abstract :
Relational databases are well suited for vertical
scaling; however, specialized hardware can be expensive. Conversely,
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 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 mechanisms to identify materialized views,
and a specialized concurrency control system on top of a NoSQL
database to enable scalable data management with familiar
relational conventions. Synergy trades slight write performance
degradation and increased disk utilization for faster join performance
(compared to standard NoSQL databases) and improved
query expressiveness (compared to NewSQL databases).
Title of Article :
A Comparative Analysis of Materialized Views
Selection and Concurrency Control Mechanisms in
NoSQL Databases
Author/Authors :
Ashish Tapdiya , Yuan Xue , Daniel Fabbri
Author/Authors - جزئيات :