Exploring performance issues for a clinical database organized using an entity-attribute-value representation.
BACKGROUND
The entity-attribute-value representation with classes and relationships (EAV/CR) provides a flexible and simple database schema to store heterogeneous biomedical data. In certain circumstances, however, the EAV/CR model is known to retrieve data less efficiently than conventionally based database schemas.


OBJECTIVE
To perform a pilot study that systematically quantifies performance differences for database queries directed at real-world microbiology data modeled with EAV/CR and conventional representations, and to explore the relative merits of different EAV/CR query implementation strategies.


METHODS
Clinical microbiology data obtained over a ten-year period were stored using both database models. Query execution times were compared for four clinically oriented attribute-centered and entity-centered queries operating under varying conditions of database size and system memory. The performance characteristics of three different EAV/CR query strategies were also examined.


RESULTS
Performance was similar for entity-centered queries in the two database models. Performance in the EAV/CR model was approximately three to five times less efficient than its conventional counterpart for attribute-centered queries. The differences in query efficiency became slightly greater as database size increased, although they were reduced with the addition of system memory. The authors found that EAV/CR queries formulated using multiple, simple SQL statements executed in batch were more efficient than single, large SQL statements.


CONCLUSIONS
This paper describes a pilot project to explore issues in and compare query performance for EAV/CR and conventional database representations. Although attribute-centered queries were less efficient in the EAV/CR model, these inefficiencies may be addressable, at least in part, by the use of more powerful hardware or more memory, or both.
Chen
R S
RS
Yale University, New Haven, Connecticut, USA.
Nadkarni
P
P
Marenco
L
L
Levin
F
F
Erdos
J
J
Miller
P L
PL
D003628:Database Management Systems; D019992:Databases as Topic / Q000458:organization & administration; D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods*; D008829:Microbiology; D010865:Pilot Projects