Análise de desempenho de Banco de Dados Relacionais e Não Relacionais em dados genômicos

Nowadays, advancements in molecular technology brought better equipments to obtain more DNA sequences in less time, making storage of genomic data a great challenge. As a result, the amount of genomic data generated has been increasing in a way that sequencing a single organism can generate terabytes of information. In general, genomic data processing make use of simple files as the primary means for storing these data. However, modern databases are a good alternative for improved management of these data by offering better organization, fault tolerance, use of available memory for storage, and performance, as they are made in order to optimize these tasks. Additionally, databases allow adding meta-information about the stored DNA sequences. Considering such a scenario, this paper presents and evaluates the performance of different storage strategies in three databases that belong to two different paradigms, MySQL (which belongs to the Relational Database paradigm), Cassandra, and MongoDB (which belong to Non-Relational Database paradigm). The results show that relational databases have limitations to cope with large genomic data sets. Palavras-chave: Dados genômicos, banco de dados, banco de dados relacional, banco de dados não relacional.