Graph databases like Neo4j provide significant advantages over relational databases when working with interconnected data, offering tools to uncover previously hidden relationships. A Ph.D. candidate in computer science uses Neo4j in her research on the impact assessment of schema evolution in a data warehouse context, finding it excels at capturing relationships and has a strong developer community and many new features related to security, clustering, scaling, and enterprise. Her favorite feature is graph visualization, which allows for easy path and relationship analysis, and she also uses Neo4j's REST API with Java drivers extensively in her research. She combines Neo4j with other technologies like relational schemas, Pentaho, and container orchestration, leveraging Neo4j's general representation of nodes, edges, and relationships to flatten heterogeneous artifacts. The candidate is happy to see Neo4j embracing Docker and its containerization capabilities, which have been incorporated into the database.