In a large-scale retail inventory system, MongoDB's query optimization and scaling capabilities are crucial for handling high-volume data and providing low-latency performance. To achieve this, the system uses aggregation pipelines to perform complex queries such as aggregating inventory across stores and retrieving real-time information based on user location. The system is designed to support a variety of queries, including updates and aggregations, while also ensuring eventual consistency in case of requests spread over large geographic areas. A carefully designed deployment topology, including datacenter deployment, shard key, and shard tags, is used to minimize latency and ensure high performance. By using MongoDB's tools for schema design, indexing, and sharding, the system can meet the needs of a large retailer while providing low-latency and high-performance capabilities.