Isbn: 9783656965763 - a comparison of nosql time series databases (1 Ergebnisse)

ISBN: 
Mit der Detailsuche verfeinern

Optimieren Sie Ihre Suche

  • Bücher (1)

  • Neu (1)

bis

Benutzerdefinierte Preisspanne (EUR)

bis

  • Sprache: Englisch

    Verlag: GRIN Verlag, GRIN Verlag, 2015

    3656965765 / 9783656965763

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

    Verkäufer/-in mit 5 Sternen
    Verkäufer/-in kontaktieren

    Zustand: Neu

    EUR 24,99

    EUR 60,42 Versand 
    Versand von Deutschland nach USA

    Anzahl: 1 verfügbar

    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (undergraduate) from the year 2015 in the subject Engineering - Industrial Engineering and Management, grade: 1,0, Technical University of Berlin (Wirtschaftsinformatik - Information Systems Engineering (ISE)), course: Seminar: Hot Topics in Information Systems Engineering, language: English, abstract: During the last years NoSQL databases have been developed to ad-dress the needs of tremendous performance, reliability and horizontal scalability.NoSQL time series databases (TSDBs) have risen to combine valuable NoSQL properties with characteristics of time series data encountering many use-cases. Solutions offer the efficient handling of data volume and frequency related to time series.Developers and decision makers struggle with the choice of a TSDB among a large variety of solutions. Up to now no comparison exists focusing on the specific features and qualities of those heterogeneous applications.This paper aims to deliver two frameworks for the comparison of TSDBs, firstly with a focus on features and secondly on quality. Furthermore, we apply and evaluate the frameworks on up to seven open-source TSDBs such as InfluxDB and OpenTSDB.We come to the result that the investigated TSDBs differ mainly in support- and extension related points. They share performance-enhancing techniques, time-related query capabilities and data schemas optimized for the handling of time-series data.…