How Database Interfaces Shape Agent Performance: An Empirical Study of SQL and Executable Semantic Layers

Database agents are typically built to query relational databases through SQL, but emerging semantic layers offer a fundamentally different agent-facing abstraction. We ask how the choice of agent-facing database interface shapes agent performance and failure modes. We systematically compare direct SQL access with an executable semantic-graph interface on BIRD Mini-Dev and LiveSQLBench-Lite. The results reveal that no interface dominates across workloads. On BIRD, graph settings are stronger, with the advantage increasing from 0.5 percentage points on Simple questions to 4.9 percentage points on Challenging questions. On LiveSQLBench-Lite, SQL leads by about four percentage points under both metadata conditions. Workload and agent-behavior analyses suggest that interface choice redistributes rather than eliminates reasoning difficulty: semantic structure can simplify identifying the relevant data and relationships, while analytically intensive workloads place greater pressure on constructing and finalizing queries. These findings establish the database interface as a first-class design choice for database agents and show that effective interface design depends on how reasoning complexity is allocated between reusable structure and query construction.