Native and multi-model graph databases have their own strengths and weaknesses, with native databases exceling in performance for specific use cases involving small to medium-sized datasets and complex relationships, while multi-model databases offer versatility, scalability, and cost-effectiveness by supporting multiple data models within a single platform. The choice between the two ultimately depends on the project's unique demands, operational priorities, and scalability needs, with some use cases benefiting from native graph databases' performance and others from multi-model databases' adaptability and flexibility.