INVESTIGADORES
MATEOS DIAZ Cristian Maximiliano
artículos
Título:
Persisting Big Data: The NoSQL Landscape [JCR]
Autor/es:
ALEJANDRO CORBELLINI; CRISTIAN MATEOS; ALEJANDRO ZUNINO; DANIELA GODOY; SILVIA SCHIAFFINO
Revista:
INFORMATION SYSTEMS
Editorial:
PERGAMON-ELSEVIER SCIENCE LTD
Referencias:
Lugar: Amsterdam; Año: 2016
ISSN:
0306-4379
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.
