IDEAS home Printed from https://ideas.repec.org/a/aes/infoec/v22y2018i2p25-34.html
   My bibliography  Save this article

Big Data Analytics: Analysis of Features and Performance of Big Data Ingestion Tools

Author

Listed:
  • Andreea MATACUTA

    ()

  • Catalina POPA

    ()

Abstract

The purpose of this study was to analyze the features and performance of some of the most widely used big data ingestion tools. The analysis is made for three data ingestion tools, developed by Apache: Flume, Kafka and NiFi. The study is based on the information about tool functionalities and performance. This information was collected from different sources such as articles, books and forums, provided by people who really used these tools. The goal of this study is to compare the big data ingestion tools, in order to recommend that tool which satisfies best the specific needs. Based on the selected indicators, the results of the study reveal that all tools consistently assure good results in big data ingestion, but NiFi is the best option from the point of view of functionalities and Kafka, considering the performance.

Suggested Citation

  • Andreea MATACUTA & Catalina POPA, 2018. "Big Data Analytics: Analysis of Features and Performance of Big Data Ingestion Tools," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 22(2), pages 25-34.
  • Handle: RePEc:aes:infoec:v:22:y:2018:i:2:p:25-34
    as

    Download full text from publisher

    File URL: http://revistaie.ase.ro/content/86/03%20-%20matacuta,%20popa.pdf
    Download Restriction: no

    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:aes:infoec:v:22:y:2018:i:2:p:25-34. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paul Pocatilu). General contact details of provider: http://edirc.repec.org/data/aseeero.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.