This paper presents a comprehensive bibliometric and comparative analysis of Generative Artificial Intelligence (GenAI) in Education Research by comparing landscape data from the Scopus and Web of Science (WoS) databases. The study presents a model with 8 steps, the first 6 of which were applied, which the authors identify as essential for bibliometric and comparative database analysis. The study focuses on the thematic components and their relevance related to GenAI. By utilising bibliometrics thematic maps, the research explores how the conceptual structures of documents differ between the two prominent databases, Scopus and WoS. The analysis reveals critical insights into the emerging field of GenAI within the educational research domain, shedding light on the varying perspectives and trends captured by each database. Through a meticulous examination of clusters and thematic mappings, the study uncovers the nuances in the representation of concepts such as Critical Thinking and other key themes in education research. The comparison between Scopus and WoS databases provides a rich understanding of the conceptual landscape surrounding GenAI, highlighting the diverse scholarly contributions and research trends in this evolving field. Limitations of this study are opportunities for future developments towards analysis and synthesis of one or several clusters.