International Journal of Distributed and Cloud Computing

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Comparative Analysis of Nosql Specimen with Relational Data Store for Big Data in Cloud


Affiliations
1 Jawahar Lal Nehru Technological University, Kakinada, Andhra Pradesh, India
 

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The massive amount of data collected by various fields is a challenging aspect for analysis using the available storage technologies. Relational databases are a traditional approach of data storage more suitable for structured data formats and are constrained by ACID properties. As the modern world data in the form of word documents, pdf files, audio and video formats is unstructured, where tables and schema definition is not a major concern. Relational databases such as Mysql may not be suitable to serve such Bigdata. An alternate approach is to use the emerging Nosql databases. This paper presents a comparative analysis of Nosql types such as Hbase, Mongodb, Simple DB and Big Table with relational database like Mysql and specifies their limitations when applied to real world problems. It also proposes solution to overcome these limitations using an integrated data store which serve to be beneficial over the mentioned Nosql and Mysql stores in terms of efficiently implementing simple and complex queries yielding better performance.

Keywords

Mysql, Nosql, Big Data, HBase, MongoDB, Simple DB, Big Table, Integrated Store.
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  • Agrawal, D., Das, S., & El Abbadi, A. (2011). Big data and cloud computing: Current state and future opportunities. Proceedings of the 14th International Conference on Extending Database Technology.

  • Dhar, S., & Mazumdar, S. (2014). Challenges and best practices for enterprise adoption of big data technologies. IEEE Technology Management Conference.

  • Grolinger, K., Higashino, W. A., Tiwari, A., & Capretz, M. A. M. (2013). Data management in cloud environments: NoSQL and NewSQL data stores. Journal of Cloud Computing: Advances Systems and Applications, 22(2), 1-41.

  • Gudivada, V. N., Rao, D., & Raghavan, V. V. (2014). NoSQL systems for big data management. In IEEE Computer Conference on Big Data: Promises and Problems, 48(3), 190-197.

  • Han, J., Haihong, E., Le, G., & Du, J. (2011). Survey on NoSQL database. 6th International Conference on Pervasive Computing and Application, (pp. 363-366).

  • Kulshreshta, S., & Sachdeva, S. (2014). Performance comparison for data storage-db4o and mysql databases. 7th International Conference on Contemporary Computing.

  • Naim, N. F., Yassin, A. I. M., Zamri, W. M. A. W., Sarnin, S. S. (2011). My SQL Database for storage of finger print data. 13th International Conference on Computer Modelling and Stimulation, (pp. 293-298).

  • Ramanathan, S., Goel, S., & Alagumlai, S. (2011). Comparison of cloud database: Amazon’s simple db and Google’s big table. International Journal of Computer Science Issues, 8(6), (pp. 243-246).

  • Sandholm, T., & Lee, D. (2014). Notes on cloud computing principles. Journal of Cloud Computing: Advances, Systems and Applications, 21(3), 1-10.

  • Vora, M. N. (2011). Hadoop-HBASE for large-scale data. International Conference on Computer Science and Network Technology, (pp. 601-605).

  • Zhao, G., Huang, W., Liang, S., & Tang, Y. (2013). Modelling mongo DB with relational model. 4th International Conference on Emerging Intelligent Data and Web Technologies, (pp. 115-121).

  • Zheng, Z., Du, Z., Li, L., & Guo, Y. (2014). Big data oriented open scalable relational data model. In IEEE International Congress on Big Data Congress (Big Data Congress), 398-405.

  • Venkat, N. (2014). What’s the future of the data center? The big list of thought leadership perspective. Silicon Angle.

  • Thomas S., Dongman, L. (2014). Notes on Cloud Computing Principles. Journal of Cloud Computing: Advances, Systems and Applications, Springer.

  • Agarwal, D., Das, S., & EI Abbadi, A. (2011). Big data and Cloud Computing: Current State and Future opportunities.

  • Grolinger, K., Higashino, W. A., Tiwari, A., & Capretz, M. A. M. (2013). Data management in cloud environments: NoSQL and NewSQL data stores. Journal of Cloud Computing, 2(1), 22.

  • Naim, F. & Yassin, I. M. (2011). MySQL Database for Storage of Fingerprint Data. Proceedings of the 13th UK Sim-AMSS International Conference on Computer Modelling and Simulation, Cambridge University, Emmanuel College, Cambridge, UK

  • Kulshreshta, S., & Sachdeva, S. (2014). Performance Comparison for Data Storage-DB4o and Mysql Databases.

  • Vora, M. N. (2011). Hadoop-H-Base for Large Scale Data. IEEE 2011, (pp. 601-605).

  • Zhao, G., Huang, W., Liang, S., & Tang, Y. (2013). Modelling Mongo DB with Relational Model. IEEE, (pp. 115-121).

  • Ramanathan, S., Goel, S., & Alagumlai, S. (2011). Comparison of Cloud Database: Amazon’s Simple DB and Googles BigTable. IEEE 2011 and International Journal of Computer Science Issues (IJCSI), November, 8(6).

  • Han, J., Hong, H. E., Le, G., & Du, J. (2011). Survey on NoSQL Databases. IEEE 2011, (pp. 363-366).

  • Zheng, Z., Du, Z., Li, L., & Guo, Y. (2014). Big Data Oriented Open Scalable Relational Data Model. IEEE Conference on Big Data Congress, )pp. 398-405).

  • Dhar, S., & Mazumdar, S. (2014). Challenges and best practices for Enterprise Adoption of Big Data Technologies. IEEE International Conference on Technology Management, (pp. 1-4).


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  • Comparative Analysis of Nosql Specimen with Relational Data Store for Big Data in Cloud

Abstract Views: 361  |  PDF Views: 173

Authors

Sangeeta Gupta
Jawahar Lal Nehru Technological University, Kakinada, Andhra Pradesh, India

Abstract


The massive amount of data collected by various fields is a challenging aspect for analysis using the available storage technologies. Relational databases are a traditional approach of data storage more suitable for structured data formats and are constrained by ACID properties. As the modern world data in the form of word documents, pdf files, audio and video formats is unstructured, where tables and schema definition is not a major concern. Relational databases such as Mysql may not be suitable to serve such Bigdata. An alternate approach is to use the emerging Nosql databases. This paper presents a comparative analysis of Nosql types such as Hbase, Mongodb, Simple DB and Big Table with relational database like Mysql and specifies their limitations when applied to real world problems. It also proposes solution to overcome these limitations using an integrated data store which serve to be beneficial over the mentioned Nosql and Mysql stores in terms of efficiently implementing simple and complex queries yielding better performance.

Keywords


Mysql, Nosql, Big Data, HBase, MongoDB, Simple DB, Big Table, Integrated Store.

References