Distributed NoSQL datastores have been developed to cater for the usage scenarios of Web 2.0 applications. These systems provide high availability through the replication of data across different machines and data centers. The performance characteristics of NoSQL datastores are determined by the degree of data replication and the consistency guarantees required by the application. This paper presents a novel performance study of the Cassandra NoSQL datastore deployed on the Amazon EC2 cloud platform. We show that a queueing Petri net model can scale to represent the characteristics of read workloads for different replication strategies and cluster sizes. We benchmark one Cassandra node and predict response times and throughput for these configurations. We study the relationship between cluster size and consistency guarantees on cluster performance and identify the effect that node capacity and configuration has on the overall performance of the cluster. © 2014 Springer International Publishing.

Modelling replication in NoSQL datastores

Piazzolla P.
2014-01-01

Abstract

Distributed NoSQL datastores have been developed to cater for the usage scenarios of Web 2.0 applications. These systems provide high availability through the replication of data across different machines and data centers. The performance characteristics of NoSQL datastores are determined by the degree of data replication and the consistency guarantees required by the application. This paper presents a novel performance study of the Cassandra NoSQL datastore deployed on the Amazon EC2 cloud platform. We show that a queueing Petri net model can scale to represent the characteristics of read workloads for different replication strategies and cluster sizes. We benchmark one Cassandra node and predict response times and throughput for these configurations. We study the relationship between cluster size and consistency guarantees on cluster performance and identify the effect that node capacity and configuration has on the overall performance of the cluster. © 2014 Springer International Publishing.
2014
Lecture Notes in Computer Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1224576
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