Evaluating the cassandra NoSQL database approach for genomic data persistency

R Aniceto, R Xavier, V Guimarães… - … journal of genomics, 2015 - Wiley Online Library
R Aniceto, R Xavier, V Guimarães, F Hondo, M Holanda, ME Walter, S Lifschitz
International journal of genomics, 2015Wiley Online Library
Rapid advances in high‐throughput sequencing techniques have created interesting
computational challenges in bioinformatics. One of them refers to management of massive
amounts of data generated by automatic sequencers. We need to deal with the persistency
of genomic data, particularly storing and analyzing these large‐scale processed data. To
find an alternative to the frequently considered relational database model becomes a
compelling task. Other data models may be more effective when dealing with a very large …
Rapid advances in high‐throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large‐scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB.
Wiley Online Library
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