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Featured Application: This study purposes a synergy approach to generate the IFC model of very large quantities of data along with its graph database. Giving the identifier to each tile, following database syntax, the historic information and metadata are merged into the graph database. This synergy approach is developed on Grasshopper and Neo4j but is also applicable to other platforms. The investigation of cultural heritage is a continuous process, in which a large scale of metadata is gradually accumulated, i.e., condition data, intervention data, and the comprehension of building techniques. We take the roof tile of Yangxindian Palace as an example. The total number of roof tiles is 17,154. Their positions are various, as they are equally distributed on double-curved irregular surfaces. Their metadata are multisource and heterogeneous. Therefore, the integration between the model and the data can be complex. This paper aims to generate the M1 (metalevel) model with its graph database based on the M3 (metalevel) model through algorithm modeling. This synergy approach consists of three parts. First is the data collection. The unique identifier is used as the index while investigating onsite, which eventually forms the metadata repository. Second is the algorithm modeling. All the roof tiles are rebuilt in Grasshopper with identifiers. Their metadata are merged through Cypher syntax, which can generate the graph database in Neo4j. Third is the delivery. The IFC model and knowledge graph are connected in real time during the whole process. The significance of this paper is to provide a synergy approach and discuss its efficiency for the integration between a model and data of very large quantities. The results show that it is efficient to express the semantic relationships of both conditions and interventions. It is practicable to lightweight the IFC model and to associate metadata into the graph database, enabling online browsing and querying. [ABSTRACT FROM AUTHOR]