The Game Discovery system uses a graph database, specifically Neo4j, to provide personalized video game recommendations. The system's data structure is based on nodes and relationships between them, where each node represents a game or characteristic, and the relationships represent connections between them. The recommendation algorithms rely heavily on the graph layout of the data, allowing for efficient querying and retrieval of relevant results. The system can be queried by searching for specific characteristics or games, and it uses techniques such as shortest path algorithms to determine relevance. By grouping relationships and summing their relevances, the system can efficiently process complex queries and provide high-quality recommendations.