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Polyglot Persistence in Data Management

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Fast and Scalable Cloud Data Management

Abstract

As applications become more data-driven and highly distributed, providing low response times to increasingly many users becomes more challenging within the scope of a single database system. Not only the variety of use cases is increasing, but also the requirements are becoming more heterogeneous: horizontal scalability, schema flexibility, and high availability are primary concerns for modern applications. While RDBMSs cover many of the functional requirements (e.g., ACID transactions and expressive queries), they cannot cover scalability, performance, and fault tolerance in the same way that specialized data stores can. The explosive growth of available systems through the Big Data and NoSQL movement sparked the idea of employing particularly well-suited database systems for subproblems of the overall application.

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Notes

  1. 1.

    Historically, there is another approach called poll-and-diff that relies on periodic query execution for discovery of result changes. However, poll-and-diff does not scale with the number of real-time query subscribers.

  2. 2.

    Baqend: https://www.baqend.com.

  3. 3.

    For an in-depth discussion of the state of the art in real-time databases, we refer to [WRG19].

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Gessert, F., Wingerath, W., Ritter, N. (2020). Polyglot Persistence in Data Management. In: Fast and Scalable Cloud Data Management. Springer, Cham. https://doi.org/10.1007/978-3-030-43506-6_7

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