Tokyo: In an ongoing effort to improve the usability of AI vector database searches within retrieval-augmented generation (RAG) systems by optimizing the use of solid-state drives (SSDs), Kioxia Corporation, a world leader in memory solutions, today announced an update to its KIOXIA AiSAQS (All-in-Storage ANNS with Product Quantization) software. This new open-source release introduces flexible controls allowing system architects to define the balance point between search performance and the number of vectors, which are opposing factors in the fixed capacity of SSD storage in the system. The resulting benefit enables architects of RAG systems to fine tune the optimal balance of specific workloads and their requirements, without any hardware modifications.

According to BERNAMA News Agency, first introduced in January 2025, KIOXIA AiSAQ software uses a novel approximate nearest neighbor search (ANNS) algorithm that is optimized for SSDs and eliminates the need to store index data in DRAM. By enabling vector searches directly on SSDs and reducing host memory requirements, KIOXIA AiSAQ technology allows vector databases to scale, largely without the restrictions caused by limited DRAM capacity.