Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

NoSQL Stores

Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_80801


NoSQL (originally referring to “non SQL”) is a new type of data management system, which, different from the conventional database systems, does not model its data using the relational tabular model. To provide a highly scalable and available data access service, NoSQL systems may adopt various data models (e.g., key-value, graph, and document) based on the applications that they are designed for. The flexibility of NoSQL’s data model makes it easier to scale to a large cluster. However, on the other hand, most NoSQL systems compromise the consistency for the scalability and availability (CAP theorem says we can only keep two features among consistency, availability, and partition tolerance). Many of them adopt the multi-version strategy and the eventual consistency model.

Applications can use the specific APIs (e.g., key based and vertex based) provided by the NoSQL system to access the data. Standard SQL is not supported, since most NoSQL systems are not designed to...

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Recommended Reading

  1. 1.
    Chang F, Dean J, Ghemawat S, Hsieh WC, Wallach DA, Burrows M, Chandra T, Fikes A, Gruber RE. Bigtable: a distributed storage system for structured data. ACM Trans Comput Syst. 2008;26(2):133.CrossRefGoogle Scholar
  2. 2.
    DeCandia G, Hastorun D, Jampani M, Kakulapati G, Lakshman A, Pilchin A, Sivasubramanian S, Vosshall P, Vogels W. Dynamo: Amazon’s highly available key-value store. In: Proceedings of the 21st ACM Symposium on Operating System Principles; 2007. p. 205–20.Google Scholar
  3. 3.
    Lakshman A, Malik P. Cassandra: structured storage system on a P2P network. In: Proceedings of the ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing; 2009. p. 5.Google Scholar
  4. 4.
    Iordanov B. HyperGraphDB: a generalized graph database. In: Proceedings of the International Conference on Web-Age Information Management; 2010. p. 25–36.CrossRefGoogle Scholar
  5. 5.
    Corbett JC, Dean J, Epstein M, Fikes A, Frost C, Furman JJ, Ghemawat S, Gubarev A, Heiser C, Hochschild P, Hsieh WC, Kanthak S, Kogan E, Li H, Lloyd A, Melnik S, Mwaura D, Nagle D, Quinlan S, Rao R, Rolig L, Saito Y, Szymaniak M, Taylor C, Wang R, Woodford D. Spanner: Google’s globally distributed database. ACM Trans Comput Syst. 2013;31(3):8.CrossRefGoogle Scholar
  6. 6.
    Cattell R. Scalable SQL and NoSQL data stores. SIGMOD Record. 2010;39(4):12–27.CrossRefGoogle Scholar
  7. 7.
    Zhang H, Chen G, Ooi BC, Tan KL, Zhang M. In-memory big data management and processing: a survey. IEEE Trans Knowl Data Eng. 2015;27(7):1920.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Zhejiang UniversityHangzhouPeople’s Republic of China

Section editors and affiliations

  • Ling Liu
    • 1
  • M. Tamer Özsu
    • 2
  1. 1.College of ComputingGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Cheriton School of Computer ScienceUniversity of WaterlooWaterlooCanada