Neo4j ( ) is a top-ranked graph database based on various metrics (DB-Engines Ranking of Graph DBMS, Hoksza & Jelínek, 2015), and has been useful in bioinformatics applications towards the research and analysis of complex biological pathways , human metabolism data and DNA interaction studies , to name a few. We found Neo4j to be useful in ingesting data from diverse databases independently and then integrating them based on our current use case. Neo4j uses property-based graph models, and hence, nodes and edges represent one or many properties associated with the same. In the context under study, tables from each database are represented as node labels, and each node under these node labels store the associated metadata as properties. For example, node 'COMPOUND_RECORDS' contains properties -Record_ID, Compound_ID, MOLREGNO, Compound_Name etc. Relationships created directly map to ontologies and schema specific to the respective databases. Starting from XML and MySQL file formats of the latest versions for DrugBank and ChEMBL respectively, the data preparation, population, and fusion are done as in our previous study .