aiqbench analysis

This article addresses a critical infrastructure challenge in large-scale AI systems by evaluating the trade-offs between memory-constrained disk-based indexes (DiskANN) and traditional RAM-resident structures like HNSW for Approximate Nearest Neighbor search. For practitioners building scalable retrieval pipelines, understanding these latency and storage dynamics is essential for managing costs without sacrificing query performance as model sizes grow.