A Logical Approach for Real Time Big Data Analytics on Heterogeneous Nosql Databases

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    NoSQL databases are developed to provide a set of new big data management features while overcoming certain limitations of relational databases. However, these databases are heterogeneous; they provide different mechanisms for storing and retrieving data, which directly affect the performance, consistency and availability of data. In addition, they offer different models of data storage, different implementations, query languages and APIs. This wide variety of platforms makes data interoperability difficult. Data interoperability can be defined as the ability of an application to interact at the same time with a set of different and heterogeneous systems. The goal of our research is to design a new approach that makes it easy for applications to analyze and explore data stored in multiple NoSQL databases. Our approach is based on a Meta model for transforming data from one model to another. Also, we have developed a common API that hides the access specificities of each NoSQL database while allowing the transformation of this data into JSON format.



  • Keywords

    Big data analytics; Interoperability; NoSQL databases; Meta model; Extraction; Transformation.

  • References

      [1] Martin, F.: Polyglot persistence (November 2011)

      [2] M. Stonebraker, “Stonebraker on nosql and enterprises,” Commun. ACM, vol. 54, no. 8, pp. 10–11, 2011.

      [3] Intel It Center , “Big Data in the Cloud: Converging Technologies, How to Create Competitive Advantage Using Cloud-Based Big Data Analytics”,2015 .

      [4] NIST Big Data Interoperability Framework: Volume 1, Definitions ,2015, http://dx.doi.org/10.6028/NIST.SP.1500-1

      [5] L. Cabibbo, “Ondm: an object-nosql datastore mapper,” Faculty of Engineering, Roma Tre University. Retrieved June15th, 2013.

      [6] F. Bugiotti, L. Cabibbo, P. Atzeni, R. Torlone ,” A Logical Approach to NoSQL Databases,” .

      [7] Pollack, M., et al.: Spring Data. Volume 1. O'Reilly Media (October 2012)

      [8] Paolo Atzeni, Francesca Bugiotti, and Luca Rossi , “Uniform access to non-relational database systems: the SOS platform”,(2012), Advanced Information Systems Engineering.

      [9] R Sellami, S Bhiri, B Defude : ODBAPI: a unified REST API for relational and NoSQL data stores , Big Data (BigData Congress), 2014 IEEE International Congress on, 653-660

      [10] T. Haselmann, G. Thies, and G. Vossen, “Looking into a rest based universal api for database-as-a-service systems,” in 12thIEEE Conference on Commerce and Enterprise Computing,CEC 2010, Shanghai, China, November 10-12, 2010,pp. 17–24.

      [11] D. Chatziantoniou :ODMC: Towards an Interoperable Big Data Universe. ACM SIGMOD Record (2013).

      [12] H. M. L. Dharmasiri , M. D. J. S. Goonetillake : federated approach on heterogeneous NoSQL data stores, International Conference on Advances in ICT for Emerging Regions (ICTer), 2013

      [13] H. Lim, Y. Han, S. Babu: How to fit when no one size fits. In: CIDR 2013, sixthBiennial Conference on Innovative Data Systems Research, Asilomar, CA, USA,January 6-9, Online Proceedings. (2013)

      [14] J. Castrejon, G. Vargas-Solar,C. Collet, R. Lozano,” Model-Driven Cloud Data Storage,”.

      [15] O Hajoui ; R Dehbi ; M Talea ; A Bakhouyi ; Z Ibn Batouta , A comparative analysis of different approaches for big data interoperability ,Third International Conference on Systems of Collaboration (SysCo),2016

      [16] M ZAHARIA et al., Apache Spark:A Unified Engine for Big Data Processing”, COMMUNICATIONS OF THE ACM NOVEMBER 2016, VOL. 59 NO. 11.

      [17] https://spark.apache.org/, 2018

      [18] https://hadoop.apache.org/




Article ID: 23236
DOI: 10.14419/ijet.v7i4.32.23236

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.