Being Logical or Going with the Flow? A Comparison of Complex Event Processing Systems

  • Elias Alevizos
  • Alexander Artikis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8445)


Complex event processing (CEP) is a field that has drawn significant attention in the last years. CEP systems treat incoming information as flows of time-stamped events which may be structured according to some underlying pattern. Their goal is to extract in real-time those patterns or even learn the patterns which could lead to certain outcomes. Many CEP systems have already been implemented, sometimes with significantly different approaches as to how they represent and handle events. In this paper, we compare the widely used Esper system which employs a SQL-based language, and RTEC which is a dialect of the Event Calculus.


Maximal Interval Sharp Turn Union Operation Complex Event Processing Event Calculus 
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  1. 1.
    Esper reference document, (accessed: January 21, 2014)
  2. 2.
    Artikis, A., Sergot, M.J., Paliouras, G.: Run-time composite event recognition. In: DEBS, pp. 69–80 (2012)Google Scholar
  3. 3.
    Artikis, A., Weidlich, M., Gal, A., Kalogeraki, V., Gunopulos, D.: Self-adaptive event recognition for intelligent transport management. In: 2013 IEEE International Conference on Big Data, pp. 319–325 (2013)Google Scholar
  4. 4.
    Balis, B., Kowalewski, B., Bubak, M.: Real-time grid monitoring based on complex event processing. Future Generation Computer Systems 27(8), 1103–1112 (2011)CrossRefGoogle Scholar
  5. 5.
    Cugola, G., Margara, A.: Processing flows of information: From data stream to complex event processing. ACM Comput. Surv. 44(3), 15 (2012)CrossRefGoogle Scholar
  6. 6.
    Etzion, O., Niblett, P.: Event Processing in Action. Manning Publications Company (2010)Google Scholar
  7. 7.
    Grabs, T., Lu, M.: Measuring performance of complex event processing systems. In: Nambiar, R., Poess, M. (eds.) TPCTC 2011. LNCS, vol. 7144, pp. 83–96. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  8. 8.
    Kowalski, R.A., Sergot, M.J.: A logic-based calculus of events. New Generation Comput. 4(1), 67–95 (1986)CrossRefGoogle Scholar
  9. 9.
    Ku, T., Zhu, Y., Hu, K.: Semantics-based complex event processing for RFID data streams. In: The First International Symposium on Data, Privacy, and E-Commerce, ISDPE 2007, pp. 32–34 (2007)Google Scholar
  10. 10.
    Mendes, M.R.N., Bizarro, P., Marques, P.: A performance study of event processing systems. In: Nambiar, R., Poess, M. (eds.) TPCTC 2009. LNCS, vol. 5895, pp. 221–236. Springer, Heidelberg (2009)Google Scholar
  11. 11.
    Mendes, M.R., Bizarro, P., Marques, P.: Towards a standard event processing benchmark. In: Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering, ICPE 2013, pp. 307–310. ACM, New York (2013)Google Scholar
  12. 12.
    Voisard, A., Ziekow, H.: Architect: A layered framework for classifying technologies of event-based systems. Inf. Syst. 36(6), 937–957 (2011)CrossRefGoogle Scholar
  13. 13.
    Weber, S., Lowe, H.J., Malunjkar, S., Quinn, J.: Implementing a real-time complex event stream processing system to help identify potential participants in clinical and translational research studies. In: AMIA Annu Symp Proc., pp. 472–476 (2010), PMID: 21347023 PMCID: PMC3041381Google Scholar
  14. 14.
    Wu, E., Diao, Y., Rizvi, S.: High-performance complex event processing over streams. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pp. 407–418. ACM (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Elias Alevizos
    • 1
  • Alexander Artikis
    • 1
  1. 1.National Centre for Scientific Research (NCSR) “Demokritos”AthensGreece

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