Native graph databases are designed to be highly optimized for storing and processing graph data, offering advantages in performance, scalability, and efficiency compared to non-native graph technologies. Native graph databases store and process data as a graph, allowing for efficient navigation of relationships and connections within the data. They use index-free adjacency, which enables direct referencing of adjacent nodes without the need for indexes, resulting in faster query times and improved scalability. Non-native graph databases, on the other hand, are built on top of non-graph technologies, such as relational or NoSQL databases, and can struggle to handle large, interconnected datasets efficiently. Understanding the differences between native and non-native graph technology is crucial when evaluating databases for specific use cases.