Abstract
To be able to handle big data workloads, modern NoSQL database management systems like Cassandra are designed to scale well over multiple machines. However, with each additional machine in a cluster, the likelihood for hardware failure increases. In order to still achieve high availability and fault tolerance, the data needs to be replicated within the cluster. Predictable and stable response times are required by many applications even in the case of a node failure. While Cassandra guarantees high availability, the influence of a node failure on the system performance is still unclear.
In this paper, we therefore focus on the availability and fault tolerance of Cassandra. We analyze the impact of a node outage within a Cassandra cluster on the throughput and latency for different workloads. Our results show that Cassandra is well suited to achieve high availability while preserving table response times in case of a node failure. Especially for read intensive applications that require high availability, Cassandra is a good choice.
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Notes
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YCSB Cassandra binding based on CQL: https://github.com/jbellis/YCSB.
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Rosselli, M., Niemann, R., Ivanov, T., Tolle, K., Zicari, R.V. (2016). Benchmarking the Availability and Fault Tolerance of Cassandra. In: Rabl, T., Nambiar, R., Baru, C., Bhandarkar, M., Poess, M., Pyne, S. (eds) Big Data Benchmarking. WBDB WBDB 2015 2015. Lecture Notes in Computer Science(), vol 10044. Springer, Cham. https://doi.org/10.1007/978-3-319-49748-8_5
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DOI: https://doi.org/10.1007/978-3-319-49748-8_5
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