DBA-Bench

DBA-Bench: Production-fidelity benchmark for LLM-based database operations agents

Researchers introduce DBA-Bench, a benchmark designed to evaluate LLM-based database agents under production-realistic conditions using live PostgreSQL environments with active workloads, persistent state, and multi-source observations. The benchmark covers 106 scenarios across seven task domains and evaluates nine baseline groups including two GPT-5.5-backed database agents and a Human DBA reference. Results reveal a stark capability gap: the best automated system achieves only 17.9% Safe Pass rate versus 93.4% for human DBAs, with performance dropping from 19.6% on Easy to 7.6% on Hard scenarios. The work highlights that current LLM agents fall far short of production-grade database operations, particularly for safe end-to-end fault remediation.