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Computer Science

NoSQL database systems: a survey and decision guidance

Profile image of Wolfram WingerathWolfram Wingerath

2016, Computer Science - Research and Development

https://doi.org/10.1007/S00450-016-0334-3
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17 pages

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Abstract

Today, data is generated and consumed at unprecedented scale. This has lead to novel approaches for scalable data management subsumed under the term NoSQL database systems to handle the everincreasing data volume and request loads. However, the heterogeneity and diversity of the numerous existing systems impede the well-informed selection of a data store appropriate for a given application context. Therefore, this article gives a top-down overview of the eld: Instead of contrasting the implementation specics of individual representatives, we propose a comparative classication model that relates functional and non-functional requirements to techniques and algorithms employed in NoSQL databases. This NoSQL Toolbox allows us to derive a simple decision tree to help practitioners and researchers lter potential system candidates based on central application requirements.

Key takeaways
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  1. The article introduces a NoSQL Toolbox for selecting appropriate NoSQL systems based on application requirements.
  2. NoSQL systems are categorized by data models: key-value, document, and wide-column stores.
  3. The CAP theorem outlines trade-offs between consistency, availability, and partition tolerance in distributed systems.
  4. PACELC extends the CAP theorem by addressing trade-offs during normal operation and partitions.
  5. Sharding and replication techniques are crucial for achieving scalability and fault tolerance in NoSQL databases.

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