IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1908.03206.html
   My bibliography  Save this paper

Managing the Complexity of Processing Financial Data at Scale -- an Experience Report

Author

Listed:
  • Sebastian Frischbier
  • Mario Paic
  • Alexander Echler
  • Christian Roth

Abstract

Financial markets are extremely data-driven and regulated. Participants rely on notifications about significant events and background information that meet their requirements regarding timeliness, accuracy, and completeness. As one of Europe's leading providers of financial data and regulatory solutions vwd processes a daily average of 18 billion notifications from 500+ data sources for 30 million symbols. Our large-scale geo-distributed systems handle daily peak rates of 1+ million notifications/sec. In this paper we give practical insights about the different types of complexity we face regarding the data we process, the systems we operate, and the regulatory constraints we must comply with. We describe the volume, variety, velocity, and veracity of the data we process, the infrastructure we operate, and the architecture we apply. We illustrate the load patterns created by trading and how the markets' attention to the Brexit vote and similar events stressed our systems.

Suggested Citation

  • Sebastian Frischbier & Mario Paic & Alexander Echler & Christian Roth, 2019. "Managing the Complexity of Processing Financial Data at Scale -- an Experience Report," Papers 1908.03206, arXiv.org.
    • Handle: RePEc:arx:papers:1908.03206
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1908.03206
    File Function: Latest version
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sebastian Frischbier & Jawad Tahir & Christoph Doblander & Arne Hormann & Ruben Mayer & Hans-Arno Jacobsen, 2022. "The DEBS 2022 Grand Challenge: Detecting Trading Trends in Financial Tick Data," Papers 2206.13237, arXiv.org.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1908.03206. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.