Skip to main content

Performance Comparison of State of Art NoSql Technologies Using Apache Spark

  • Conference paper
  • First Online:
Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 869))

Included in the following conference series:

Abstract

Data is the new currency of digital world today. Data generated in last 2 years are more in size as compared to data generated in last 15 years. The nature of data generated have varying dimensions, size, speed and behavior along with being semi and full unstructured, it also contains various formats including text, document, excel, power point, web blogs, posts, chats, tweets, audio and video streams and long range numeric values, etc. Storing such type of data in legacy SQL based storage will not yield the benefit of currency. To take full advantage of data the IT industry is equipped with variety of State of Art NoSql (Not only Sql) databases. Each of them has their own specific features and limitations. In this research we have conducted an experiment on state of art NoSql technologies to find out a comparative analysis among them on the basis of performance, integration, ease of use and size of data loading/unloading capabilities. For experiment we used 3.4 TB of data which contains medical test records, lab diagnostics and prescriptions, long range pi values. The generated data was stored in AeroSpike, BerkeleyDB, CouchBase, HBase, MongoDB and Redis. The performance testing was done on queries like search in, equate, greater than, less than and other general arithmetic operations, etc. Those queries were executed using the Apache Spark on a cluster with a processing capacity of 54 cores and memory of 168 GB. The comparison provided some useful and defining results towards selection of NoSql stores for specific nature of jobs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bhogal, J., Choksi, I.: 2015 IEEE 29th International Conference on Handling big data using NoSQL. In: Advanced Information Networking and Applications Workshops (WAINA), pp. 24–27, March 2015

    Google Scholar 

  2. Abidin, S.Z.Z., Idris, N.M.: Extraction and classification of unstructured data in webpages for structured multimedia database via XML. In: 2010 International Conference on Information Retrieval & Knowledge Management, (CAMP), 17–18 March 2010

    Google Scholar 

  3. Fu, J., Sun, J.: SPARK—A Big Data Processing Platform for Machine Learning. In: 2016 International Conference on Industrial Informatics—Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), 3–4 December 2016

    Google Scholar 

  4. Maheshwar, R.C., Haritha, D.: Survey on high performance analytics of bigdata with Apache spark. In: 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), 25–27 May 2016

    Google Scholar 

  5. Srinivasan, V., Sayyaparaju, S., Shinde, A.: Aerospike: architecture of a Real-Time operational DBMS, Aerospike, Inc.vldb (2016)

    Google Scholar 

  6. Lourenço, J.R.: Choosing the right NoSQL database for the job: a quality attribute evaluation. J. Big Data 2, 18 (2015)

    Article  Google Scholar 

  7. Berkeley, D.B.: Reference Guide: what is Berkeley DB not? http://www2.gnu-darwin.org/.org, 31 May 2001. Retrieved on 18 Sep 2013

  8. http://doc.gnu-darwin.org/am_misc/dbsizes.html Berkeley DB Reference Guide: Database limits Retrieved on 19 Sep 2013

  9. Kuznetsov, S., Poskonin, A.: Nosql data management systems. Program. Comput. Softw. 40(6), 323–332 (2014)

    Article  Google Scholar 

  10. Haughian, G.: Benchmarking replication in Nosql data stores. Dissertation, Imperial College London (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anwar ul Haque .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

ul Haque, A., Mahmood, T., Ikram, N. (2019). Performance Comparison of State of Art NoSql Technologies Using Apache Spark. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_44

Download citation

Publish with us

Policies and ethics