It boils down to whether your LLMs can speak graph queries better than SQL, for your use cases and data. As your data posture changes and your use cases change, you routinely reevaluate which DB query language suits best for LLMs.
I'd also design the system architecture in such a way that your non-agentic workloads don't suffer if you have to move between query models for serving agentic workloads better.
I'd also design the system architecture in such a way that your non-agentic workloads don't suffer if you have to move between query models for serving agentic workloads better.