NoSQL databases such as Apache Cassandra have attracted large
interest in recent years thanks to their high availability, scalability,
flexibility and low latency. Still there is limited research work on
performance engineering methods for NoSQL databases, which yet
are needed since these systems are highly distributed and thus can
incur significant cost/performance trade-offs. To address this need,
we propose a novel queueing network model for the Cassandra
NoSQL database aimed at supporting resource provisioning. The
model defines explicitly key configuration parameters of Cassandra
such as consistency levels and replication factor, allowing engineers
to compare alternative system setups.
Experimental results based on the YCSB benchmark indicate that,
with a small amount of training for the estimation of its input param-
eters, the proposed model achieves good predictive accuracy across
different loads and consistency levels. The average performance
errors of the model compared to the real results are between 6% and
10%. We also demonstrate the applicability of our model to other
NoSQL databases and other possible utilisation of it.