Wer nutzt diese Software?

Data driven organizations.

Durchschnittliche Bewertung

1 Bewertung
  • Gesamt 4 / 5
  • Benutzerfreundlichkeit 4 / 5
  • Kundenservice 4 / 5
  • Funktionen 4 / 5
  • Preis-Leistungs-Verhältnis 4 / 5


  • Kostenlose Version Ja
  • Kostenlose Testversion Ja
  • Einsatz Cloud, SaaS, Web
    Installiert - Windows
  • Training Persönlich
    Live Online
  • Kundenbetreuung 24/7 (Live Vertreter)
    Support während der Geschäftszeiten

Angaben zum Hersteller

  • Kyvos Insights
  • http://www.kyvosinsights.com
  • Gegründet 2014

Über BI on Big Data

Kyvos is a disruptive Big Data solution that delivers the fastest BI on the planet at massive scale. Our patent-pending OLAP technology enables Fortune 500 companies to query billions of rows of data within seconds and helps business leaders make informed decisions. We harness the true potential of data lakes in partnership with industry leaders in BI, Cloud, and Hadoop technologies. Kyvos has been shown to be 100x faster than Hive and Impala on standard benchmarks.

BI on Big Data Funktionen

  • Codefreie Sandbox
  • Data Mining
  • Data Warehousing (Datenlager)
  • Daten mischen
  • Datenbereinigung
  • Datenvisualisierung
  • Kollaboration
  • Prädiktive Analytik
  • Verarbeitung von hohen Volumen
  • Vorlagen

Die hilfreichsten Reviews für BI on Big Data

HDFS files are write once files. I consider HDFS files as write-once and read-many files

Mit Google übersetzen Bewertet am 7.6.2017
Rakesh M.
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
4 / 5
4 / 5
Eigenschaften & Funktionalitäten
4 / 5
4 / 5
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Vorteile: I like MapReduce code a lot. Mappers and Reducers and how the overall hierarchy goes by. Hadoop is a platform that I have chosen a year ago and still I am in love with it because of it's simplicity for solving complex problems involving very large database. I also did Apache Giraph which goes into graph processing and was a great experience learning a whole new product of Hadoop. I like solving real life challenges using Hadoop like predicting earthquakes so that the results could be less devastating. This is one of my proposed ideas but there are many more like these which I like a lot.

Nachteile: HDFS doesn't do random reads very well. A caveat of HDFS to remember, it is a distributed file system abstracted on top of local file system by hadoop, suitable for storing huge files; however, it does not provide facility of tabular form of storage as such.

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