Accelerating Similarity Search on Really Big Data with Vector Indexing

What this post added

This post details the role of vector indexing in accelerating similarity search, focusing on different Vector Inverted File (IVF) index types: FLAT, IVF_FLAT, IVF_SQ8, and IVF_SQ8H. It provides performance test results for query time and recall rates for each index type in Milvus, offering guidance on selecting the best index for various scenarios based on dataset size, accuracy requirements, and resource availability. It also introduces the concept of scalar quantization in IVF_SQ8 for reduced resource consumption.