Abstract
Document-oriented database systems, also known as document stores, are attractive for building modern web applications where the speed of development and deployment are critical, especially due to the prevalence of data in document-structured formats such as JSON and XML. MongoDB Atlas is a hosted offering of MongoDB as a Service, which is easy to set up, operate, and scale in the cloud. Like many NoSQL stores, MongoDB Atlas allows users to accept possible temporary inconsistency among the replicas, as a trade-off for lower latency and higher availability during partitions. In this work, we describe an empirical study to quantify the amount of inconsistency observed in data that is held in MongoDB Atlas.
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Acknowledgments
This research forms part of the Australian Research Council (ARC) Linkage Project LP160100883. We thank Gary Little, Shahram Ghandeharizadeh, and Raghunath Nambiar for their comments on this paper. We also thank AWS Cloud Research Credits for their support.
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Huang, C., Cahill, M., Fekete, A., Röhm, U. (2019). Data Consistency Properties of Document Store as a Service (DSaaS): Using MongoDB Atlas as an Example. In: Nambiar, R., Poess, M. (eds) Performance Evaluation and Benchmarking for the Era of Artificial Intelligence. TPCTC 2018. Lecture Notes in Computer Science(), vol 11135. Springer, Cham. https://doi.org/10.1007/978-3-030-11404-6_10
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DOI: https://doi.org/10.1007/978-3-030-11404-6_10
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