Standard SQL Approaches for Similarity Searching

Abstract

This paper addresses complex data storage and retrieval in RDBMS, which depends on metric distance functions for the assessment of data dissimilarity. However, both the empirical analysis of strategies for complex data storage and the definition of a suitable representation for similarity query operators are still open issues in the literature. Here, we fulfill those gaps through the classification, implementation, and evaluation of existing approaches for complex data storage according to four structures found in standard SQL, namely relational, object-relational, binary and semi-structured. Moreover, we also discuss a comprehensive model for complex data retrieval, whose conception of similarity operators is consistent with standard SQL representations. Accordingly, a distance function representation is presented, which enables the RDBMS query processor to interpret and execute physical similarity operators. Experimental results indicate: (i) relational and object-relational structures outperform the other two competitors in the majority of scenarios, whereas (ii) object-relational strategy enables the use of a broader representation.