Artículos de revistas
Persisting big-data: The NoSQL landscape
Fecha
2017-01Registro en:
Corbellini, Alejandro; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Godoy, Daniela Lis; Schiaffino, Silvia Noemi; Persisting big-data: The NoSQL landscape; Pergamon-Elsevier Science Ltd; Information Systems; 63; 1-2017; 1-23
0306-4379
CONICET Digital
CONICET
Autor
Corbellini, Alejandro
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
Godoy, Daniela Lis
Schiaffino, Silvia Noemi
Resumen
The growing popularity of massively accessed Web applications that store and analyze large amounts of data, being Facebook, Twitter and Google Search some prominent examples of such applications, have posed new requirements that greatly challenge traditional RDBMS. In response to this reality, a new way of creating and manipulating data stores, known as NoSQL databases, has arisen. This paper reviews implementations of NoSQL databases in order to provide an understanding of current tools and their uses. First, NoSQL databases are compared with traditional RDBMS and important concepts are explained. Only databases allowing to persist data and distribute them along different computing nodes are within the scope of this review. Moreover, NoSQL databases are divided into different types: Key-Value, Wide-Column, Document-oriented and Graph-oriented. In each case, a comparison of available databases is carried out based on their most important features.