Scalability of Facebook Architecture

  • Hugo BarrigasEmail author
  • Daniel Barrigas
  • Melyssa Barata
  • Jorge Bernardino
  • Pedro Furtado
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 353)


Scalability is the ability of a system, network, or process to handle a growing amount of work in a capable manner or its ability to be enlarged to accommodate that growth. There are a lot of different elements behind the success of Facebook. Of course it’s mostly about vision, timing and the right people. It’s also about the availability of readily available technology and excellent technical architecture. This paper addresses and compares both scalable and non-scalable systems. The purpose of this paper is to present a scalable web interaction benchmarking setup, using as a case study a simulation of Facebook, and to explain Facebook’s main architecture.


Scalability Facebook Benchmark Architecture 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Beaver, D., Kumar, S., Li, H.C., Sobel, J., Vajgel, P.: Finding a Needle in Haystack: Facebook’s Photo Storage. In: OSDI, pp. 47–60 (2010)Google Scholar
  2. 2.
    Facebook passes 1.23 billion monthly active users, 945 million mobile users, and 757 million daily users, (accessed October 16, 2014)
  3. 3.
    Hilsen, A.I., Helvik, T.: The construction of self in social medias, such as Facebook. Al. Soc. 29(1), 3–10 (2014)CrossRefGoogle Scholar
  4. 4.
    How Does Facebook Work? The Nuts and Bolts (Technology Explained), (accessed February 25, 2014)
  5. 5.
    Jose, J., Subramoni, H., Luo, M., Zhang, M., Huang, J., Rahman, W., Islam, N.S., Ouyang, X., Wang, H., Sur, S., Panda, D.K.: Memcached Design on High Performance RDMA Capable Interconnects. In: ICPP, pp. 743–752 (2011)Google Scholar
  6. 6.
    Lewis, K., Gonzalez, J., Wimmer, A., Christakis, N.: Tastes, ties, and time: A new social network dataset using Social Networks 30(4), 330–342 (2008)CrossRefGoogle Scholar
  7. 7.
    Garrod, C., Manjhi, A., Ailamaki, A., Maggs, B., Mowry, T., Olston, C., Tomasic, A.: Query Result Caching for Web Applications. PVLDB 1(1), 550–561 (2008)Google Scholar
  8. 8.
    Scaling the Messages Application Back End, (accessed February 25, 2014)
  9. 9.
    Schram, A., Anderson, K.M.: MySQL to NoSQL Data Modeling Challenges in Supporting Scalability. In: SPLASH, pp. 191–202 (2012)Google Scholar
  10. 10.
    Thusoo, A., Sarma, J.S., Jain, N., Shao, Z., Chakka, P., Zhang, N., Anthony, S., Liu, H., Murthy, R.: Hive - a petabyte scale data warehouse using Hadoop. In: ICDE, pp. 996–1005 (2010)Google Scholar
  11. 11.
    Web application performance and scalability, (accessed January 30, 2014)
  12. 12.
    Yang, B., Tsai, W., Chen, A., Ramandeep, S.: Cloud Computing Architecture for Social Computing - A Comparison Study of Facebook and Google. In: ASONAM, pp. 741–745 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Hugo Barrigas
    • 2
    Email author
  • Daniel Barrigas
    • 2
  • Melyssa Barata
    • 1
  • Jorge Bernardino
    • 1
    • 2
  • Pedro Furtado
    • 2
  1. 1.Polytechnic Institute of CoimbraCoimbraPortugal
  2. 2.University of Coimbra Pinhal de MarrocosCoimbraPortugal

Personalised recommendations