The recent growing of the Semantic Web requires the need to cope with highly semantic heterogeneities among available ontologies . The Semantic Web envisions a metadata-rich Web where presently human-readable content will have machine-understandable semantics. Ontology matching techniques aim to tackle heterogeneity by establishing correspondences between ontologies' elements. An intricate obstacle faces the ontology matching problem is its scalability against large number and large-scale ontologies . This paper is comparative analysis among the different matching algorithms that tackle heterogeneity and recommend the algorithms that would fit for highly scalable systems.