Criteria to Compare Cloud Computing with Current Database Technology

  • Jean-Daniel Cryans
  • Alain April
  • Alain Abran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5338)


After Google published their first paper on their software infrastruc-ture in October 2003, the open-source community quickly began working on similar free solutions. Yahoo! is now able to process terabytes of data daily using Hadoop, which is a scalable distributed file system and an open-source implementation of Google’s MapReduce. HBase, a distributed database that uses Hadoop, enables the reliable storage of structured data, just like Google’s Bigtable which powers applications like Google Maps and Google Analytics, to name only two. Many companies are tempted to use these technologies, but it is currently difficult to compare today’s systems with systems built on top of HBase. This paper presents this new technology and, a list of proposed comparison elements to existing database technology as well as proposed comparison assessment criteria.


Cloud Computing Bigtable HBase Hadoop 


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  1. 1.
  2. 2.
    HADOOP.COM. Product page,
  3. 3.
    HBASE.ORG. Product page,
  4. 4.
    Chang, F., Dean, J., Ghemawat, S., et al.: Bigtable: A Distributed Storage System for Structured Data. In: 7th Symposium on Operating Systems Design and Implementation (OSDI 2006), Seattle, WA, USA, November 6-8, pp. 205–218 (2006)Google Scholar
  5. 5.
    Cordes, K.: YouTube scalability Talk (July 14, 2007),
  6. 6.
    Ghemawat, S., Gobioff, H., Leung, S.-T.: The Google file system. In: Proc. of the 19th ACM SOSP, December 2003, pp. 29–43 (2003)Google Scholar
  7. 7.
    Dean, J., Ghemawat, S.: MapReduce: Simplified data processing on large clusters. In: Proc. of the 6th OSDI, December 2004, pp. 137–150 (2004)Google Scholar
  8. 8.
    Burrows, M.: The Chubby lock service for loosely coupled distributed systems. In: Proc. of the 7th OSDI (November 2006)Google Scholar
  9. 9.
    YAHOO.COM. Product page,
  10. 10.
    APACHE.ORG. Product page,
  11. 11.
    Baldeschwieler, E.: Yahoo! Launches world’s biggest Hadoop production application (February 19, 2008),
  12. 12.
    Borthakur, D.: The Hadoop Distributed File System: Architecture and Design (May 21, 2008),
  13. 13.
    Dean, J., Ghemawat, S.: MapReduce: Simplified data processing on large clusters. Communications of the ACM 51(1) (January 2008)Google Scholar
  14. 14.
    Hood, S.: MapReduce at Rackspace (January 23, 2008),
  15. 15.
    List of companies using Hadoop (June 6, 2008),
  16. 16.
    Reed, B.: Zookeeper (March 25, 2008),
  17. 17.
  18. 18.
    Delap, S.: HBase Leads Discuss Hadoop, BigTable and Distributed Databases (April 28, 2008),
  19. 19.
    Hoff, T.: How to learn to stop worrying and use lots of disk space to scale (May 21, 2008),
  20. 20.
    FACEBOOK.COM. Product page,
  21. 21.
    HADOOP.CA. Product page,
  22. 22.
    Unknown author, Hadoop MapReduce Tutorial (May 21, 2008),
  23. 23.
    ISO/IEC 9126:1999. Software Engineering – Product quality. Int. Org. for Standardization, ISO 9126 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jean-Daniel Cryans
    • 1
  • Alain April
    • 1
  • Alain Abran
    • 1
  1. 1.École de Technologie SupérieureMontréalCanada

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