Examining database persistence of ISO/EN 13606 standardized electronic health record extracts: relational vs. NoSQL approaches.
BMC Med Inform Decis Mak
; 17(1): 123, 2017 Aug 18.
Article
en En
| MEDLINE
| ID: mdl-28821246
ABSTRACT
BACKGROUND:
The objective of this research is to compare the relational and non-relational (NoSQL) database systems approaches in order to store, recover, query and persist standardized medical information in the form of ISO/EN 13606 normalized Electronic Health Record XML extracts, both in isolation and concurrently. NoSQL database systems have recently attracted much attention, but few studies in the literature address their direct comparison with relational databases when applied to build the persistence layer of a standardized medical information system.METHODS:
One relational and two NoSQL databases (one document-based and one native XML database) of three different sizes have been created in order to evaluate and compare the response times (algorithmic complexity) of six different complexity growing queries, which have been performed on them. Similar appropriate results available in the literature have also been considered.RESULTS:
Relational and non-relational NoSQL database systems show almost linear algorithmic complexity query execution. However, they show very different linear slopes, the former being much steeper than the two latter. Document-based NoSQL databases perform better in concurrency than in isolation, and also better than relational databases in concurrency.CONCLUSION:
Non-relational NoSQL databases seem to be more appropriate than standard relational SQL databases when database size is extremely high (secondary use, research applications). Document-based NoSQL databases perform in general better than native XML NoSQL databases. EHR extracts visualization and edition are also document-based tasks more appropriate to NoSQL database systems. However, the appropriate database solution much depends on each particular situation and specific problem.Palabras clave
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Banco de datos:
MEDLINE
Asunto principal:
Sistemas de Administración de Bases de Datos
/
Almacenamiento y Recuperación de la Información
/
Registros Electrónicos de Salud
Idioma:
En
Año:
2017
Tipo del documento:
Article