Size KDB.AI vector indexes

Guide KDB.AI sizing, capacity planning, and server resource configuration by collecting dataset and usage requirements, recommending suitable vector indexes and starting configurations, and estimating RAM, GPU VRAM, and persisted disk. Use for KDB.AI hardware requirements, capacity planning, memory-fit questions, row/vector limits, sizing from a data-volume figure (size per day or total size) rather than a row count, index selection, whether and how to partition a table (partition-key selection, the partition_column, and how partition scope works), qHnsw mmap sizing, CAGRA GPU sizing, and CPU worker/thread configuration — including standalone NUM_WRK and THREADS worker/th…