A workload consists of short interactive BI queries that run frequently. Which Presto engine configuration is most appropriate?

Interactive BI workloads need consistent low-latency responses; a properly sized always-on Presto engine avoids startup delays; while large batch-optimized engines would waste resources on short queries. The incorrect options ("A large multi-node cluster with maximum memory optimized for batch processing", "A Spark engine configured for iterative machine learning workloads", "A paused engine that is started manually for each query session") are distractors that don't fully capture the concept described.