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  • 标题:Big Data Performance and Comparison with Different DB Systems
  • 本地全文:下载
  • 作者:Matteo D’Aloia ; Ruggero Russo ; Gianpaolo Cice
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2017
  • 卷号:8
  • 期号:1
  • 页码:59-63
  • 出版社:TechScience Publications
  • 摘要:In this work we analyze the computational costs ofwrite, read and delete operations for five database (DB)systems. Starting from a complete overview of databasesystems, two standard DB systems, such as MySQL andPostgres, and three Big Data systems such as Hbase,Cassandra and MongoDB have been analyzed. Thecomputation time estimation has been performed for a singlenode implementation and for the computation of 50.000 and1.000.000 records. The operations has been executed onrandom data. Authors found best performances for CassandraDB system performing, for 1.000.000 records, an averagecomputational time of: 1,46’’ for reading, 5’58’’ for writing,and 1’05’’ for deleting.
  • 关键词:Big Data; DB; DBMS; DB performances
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