How to Cut Vector Database Costs by Up to 80%: A Practical Milvus Optimization Guide

What this post added

This post details practical optimization strategies for reducing Milvus infrastructure costs, focusing on memory optimization. It introduces and explains the configuration of MMap (Memory-Mapped Files) and Tiered Storage as methods to significantly reduce memory usage by leveraging local disk and object storage. It also highlights the impact of index selection (e.g., IVF_SQ8 vs. HNSW) and embedding dimensionality on cost. The post provides configuration examples for MMap and Tiered Storage in Milvus.