Managing Data in Massive-Scale Vector Search Engine

This post details Milvus's data management strategies for massive-scale vector search. It explains vector insertion using a mutable buffer that flushes to disk regularly, similar to Elasticsearch. It describes the creation and merging of Raw Data Files to manage fragmentation and the process of building Index Files for efficient search, contrasting them with raw data. The post also covers Meta Data management using SQLite/MySQL to track file statuses and operations, and introduces the Query Scheduler for optimizing hardware resource utilization during searches, including 'cold' vs. 'warm' queries and LRU for data replacement. Finally, it touches upon the Result Reducer for combining search results.