Advertisement

Computing

, Volume 102, Issue 1, pp 221–246 | Cite as

Bringing SQL databases to key-based NoSQL databases: a canonical approach

  • Geomar A. SchreinerEmail author
  • Denio Duarte
  • Ronaldo dos Santos Mello
Article

Abstract

Big Data management has brought several challenges to data-centric applications, like the support to data heterogeneity, rapid data growth and huge data volume. NoSQL databases have been proposed to tackle Big Data challenges by offering horizontal scalability, schemaless data storage and high availability, among others. However, NoSQL databases do not have a standard query language, which bring on a steep learning curve for developers. On the other hand, traditional relational databases and SQL are very popular standards for storing and manipulating critical data, but they are not suitable to Big Data management. One solution for relational-based applications to move to NoSQL databases is to offer a way to access NoSQL databases through SQL instructions. Several approaches have been proposed for translating relational database schemata and operations to equivalent ones in NoSQL databases in order to improve scalability and availability. However, these approaches map relational databases only to a single NoSQL data model and, sometimes, to a specific NoSQL database product. This paper presents a canonical approach, called SQLToKeyNoSQL, that translates relational schemata as well as SQL instructions to equivalent schemata and access methods of any key-oriented NoSQL database. We present the architecture of our layer focusing on the mapping strategies as well as experiments that evaluate the benefits of our approach against some state-of-art baselines.

Keywords

Data interoperability Cloud computing Relational-cloud mapping NoSQL Big data 

Mathematics Subject Classification

68P15 

Notes

References

  1. 1.
    Abadi DJ (2009) Data management in the cloud: limitations and opportunities. IEEE Data Eng Bull 32(1):3–12MathSciNetGoogle Scholar
  2. 2.
    Apache (2017) White paper: apache phoenix. http://phoenix.apache.org/. Accessed 24 Aug 2018
  3. 3.
    Arnaut DE, Schroeder R, Hara CS (2011) Phoenix: a relational storage component for the cloud. In: 2013 IEEE SICCC 0Google Scholar
  4. 4.
    Atzeni P, Bugiotti F, Rossi L (2012) Sos (save our systems): a uniform programming interface for non-relational systems. In: Proceedings of the 15th international conference on extending database technology. ACM, New YorkGoogle Scholar
  5. 5.
    Banerjee S, Goto T, Debnath NC, Sarkar A (2017) Ontology driven query language for nosql databases. In: 2017 IEEE 15th international conference on industrial informatics (INDIN), pp 951–956Google Scholar
  6. 6.
    Bisbal J, Lawless D, Wu B, Grimson J (1999) Legacy information systems: issues and directions. IEEE Softw 16(5):103–111CrossRefGoogle Scholar
  7. 7.
    Cattell R (2011) Scalable SQL and NoSQL data stores. SIGMOD Rec 39(4):12–27CrossRefGoogle Scholar
  8. 8.
    Chung WC, Lin HP, Chen SC, Jiang MF, Chung YC (2014) Jackhare: a framework for SQL to NoSQL translation using mapreduce. Autom Softw Eng 21(4):489–508CrossRefGoogle Scholar
  9. 9.
    dos Santos Ferreira G, Calil A, dos Santos Mello R (2013) On providing DDL support for a relational layer over a document NoSQL database. In: IIWAS. ACM, New YorkGoogle Scholar
  10. 10.
    Egger D (2009) SQL in the cloud. Ph.D. thesis, Master Thesis ETH ZurichGoogle Scholar
  11. 11.
    Fielding RT (2000) Architectural styles and the design of network-based software architectures. Ph.D. thesis, University of California, IrvineGoogle Scholar
  12. 12.
    Hamouda S, Zainol Z (2017) Document-oriented data schema for relational database migration to NoSQL. In: 2017 International conference on big data innovations and applications (innovate-data), pp 43–50Google Scholar
  13. 13.
    Kim HJ, Ko EJ, Jeon YH, Lee KH (2018a) Migration from RDBMS to column-oriented NoSQL: lessons learned and open problems. In: Lee W, Choi W, Jung S, Song M (eds) Proceedings of the 7th international conference on emerging databases. Springer Singapore, pp 25–33Google Scholar
  14. 14.
    Kim HJ, Ko EJ, Jeon YH, Lee KH (2018b) Techniques and guidelines for effective migration from RDBMS to NoSQL. J Supercomput.  https://doi.org/10.1007/s11227-018-2361-2 CrossRefGoogle Scholar
  15. 15.
    Lawrence R (2014) Integration and virtualization of relational SQL and NoSQL systems including MySQL and MongoDB. In: CSCI, vol 1Google Scholar
  16. 16.
    Liu ZH, Hammerschmidt BC, McMahon D (2014) JSON data management: supporting schema-less development in RDBMS. In: ICMD, SIGMODGoogle Scholar
  17. 17.
    Mishra P, Eich MH (1992) Join processing in relational databases. ACM CSUR 24(1):63–113CrossRefGoogle Scholar
  18. 18.
    Papakonstantinou Y, Garcia-Molina H, Widom J (1995) Object exchange across heterogeneous information sources. In: 11th CDE. IEEEGoogle Scholar
  19. 19.
    Rith J, Lehmayr PS, Meyer-Wegener K (2014) Speaking in tongues: SQL access to NoSQL systems. In: 29th ACM SAC, New YorkGoogle Scholar
  20. 20.
    Rocha L, Vale F, Cirilo E, Barbosa D, Mouro F (2015) A framework for migrating relational datasets to NoSQL1. Procedia Comput Sci 51(C):2593–2602CrossRefGoogle Scholar
  21. 21.
    Sadalage PJ, Fowler M (2012) NoSQL distilled: a brief guide to the emerging world of polyglot persistence. Pearson Education, LondonGoogle Scholar
  22. 22.
    Schreiner GA, Duarte D, dos Santos Mello R (2015) SQLtoKeyNoSQL: a layer for relational to key-based NoSQL database mapping. In: iiWAS, ACM, New YorkGoogle Scholar
  23. 23.
    Vathy-Fogarassy G, Hugyk T (2017) Uniform data access platform for SQL and NoSQL database systems. Inf Syst 69(C):93–105CrossRefGoogle Scholar
  24. 24.
    Vilaça R, Cruz F, Pereira J, Oliveira R (2013) An effective scalable SQL engine for NoSQL databases. In: Dowling J, Taïani F (eds) 13th IFIP, DAIS, Springer, BerlinCrossRefGoogle Scholar
  25. 25.
    Xu J, Shi M, Chen C, Zhang Z, Fu J, Liu CH (2016) ZQL: a unified middleware bridging both relational and NoSQL databases. In: 2016 IEEE 14th ICD, ASC, 14th ICPIC, 2nd CyberSciTech, pp 730–737Google Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Federal University of Santa CatarinaFlorianópolisBrazil
  2. 2.Federal University of Fronteira SulChapecóBrazil

Personalised recommendations