Service-oriented data denormalization for scalable web applications

Zhou Wei*, Jiang Dejun, Pierre Guillaume, Chi Hung Chi, Maarten van Steen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

15 Citations (Scopus)


Many techniques have been proposed to scale web applications. However, the data interdependencies between the database queries and transactions issued by the applications limit their efficiency. We claim that major scalability improvements can be gained by restructuring the web application data into multiple independent data services with exclusive access to their private data store. While this restructuring does not provide performance gains by itself, the implied simplification of each database workload allows a much more efficient use of classical techniques. We illustrate the data de-normalization process on three benchmark applications: TPC-W, RUBiS and RUBBoS. We deploy the resulting service-oriented implementation of TPC-W across an 85-node cluster and show that restructuring its data can provide at least an order of magnitude improvement in the maximum sustainable throughput compared to master-slave database replication, while preserving strong consistency and transactional properties.

Original languageEnglish
Title of host publicationWWW '08
Subtitle of host publicationProceeding of the 17th International Conference on World Wide Web 2008
Place of PublicationNew York, NY
PublisherACM Publishing
Number of pages10
ISBN (Print)978-1-60558-085-2
Publication statusPublished - 15 Dec 2008
Externally publishedYes
Event17th International World Wide Web Conference, WWW 2008 - Beijing, China
Duration: 21 Apr 200825 Apr 2008
Conference number: 17


Conference17th International World Wide Web Conference, WWW 2008
Abbreviated titleWWW


  • Data denormallzation
  • Scalability
  • Web applications


Dive into the research topics of 'Service-oriented data denormalization for scalable web applications'. Together they form a unique fingerprint.

Cite this