A developer benchmark comparison evaluates vector stores, graph databases, and SQL for production AI agent memory systems, measuring latency, recall, and operational performance under realistic loads. The analysis identifies where each approach fails and which holds up at scale, framing memory architecture choice as a critical stability factor for AI agents. The article provides runnable benchmarks to help engineers select the appropriate backend for their use case.