In this work we analyze the computational costs of write, read and delete operations for five database (DB) systems. Starting from a complete overview of database systems, two standard DB systems, such as MySQL and Postgres, and three Big Data systems such as Hbase, Cassandra and MongoDB h ave been analyzed. The computation time estimation has been performed for a single node implementation and for the computation of 50.000 and 1.000.000 records. The operat ions has been executed on random data. Authors found best performances for Cassandra DB system performing, for 1.000.000 records, an average computational time of: 1,46’’ for reading, 5’58’’ for writing, and 1’05’’ for deleting.
Big Data Performance and Comparison with Different DB Systems / D'Aloia, Matteo; Russo, Ruggero; Cice, Gianpaolo; Montingelli, Angela; Frulli, Gaetano; Frulli, Egidio; Mancini, Francesca; Rizzi, Maria; Longo, Annalisa. - In: INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGIES. - ISSN 0975-9646. - ELETTRONICO. - 8:1(2017), pp. 59-63.
Big Data Performance and Comparison with Different DB Systems
RIZZI, Maria;
2017-01-01
Abstract
In this work we analyze the computational costs of write, read and delete operations for five database (DB) systems. Starting from a complete overview of database systems, two standard DB systems, such as MySQL and Postgres, and three Big Data systems such as Hbase, Cassandra and MongoDB h ave been analyzed. The computation time estimation has been performed for a single node implementation and for the computation of 50.000 and 1.000.000 records. The operat ions has been executed on random data. Authors found best performances for Cassandra DB system performing, for 1.000.000 records, an average computational time of: 1,46’’ for reading, 5’58’’ for writing, and 1’05’’ for deleting.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
