New Open-Source Software Enables Flexible Balancing of Capacity and Performance Based on User Needs and Environment

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 today announced an update to its AiSAQ™ (All-in-Storage ANNS with Product Quantization) software. This new open-source release introduces flexible controls that allow system architects to define the balance point between search performance and the number of vectors, which are opposing factors with the fixed capacity of SSD storage in the system. The resulting benefit enables architects of RAG systems to fine-tune the optimal balance between specific workloads and their requirements, without any hardware modifications.

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.

When the installed capacity of the SSD in the system is fixed, increasing search performance (queries per second) requires more SSD capacity consumed per vector. This results in a smaller number of vectors. Conversely, to maximize the number of vectors, SSD capacity consumption per vector needs to be reduced, which results in lower performance. The optimal balance between these two opposing conditions varies depending on the specific workload. To find the appropriate balance, KIOXIA AiSAQ software introduces flexible configuration options. This latest update allows administrators to select the optimal balance for a variety of contrasting workloads among the RAG system. This update makes KIOXIA AiSAQ technology a suitable SSD-based ANNS for not only RAG applications, but also other vector-hungry applications such as offline semantic searches.

With growing demand for scalable AI services, SSDs offer a practical alternative to DRAM for managing the high throughput and low latency that RAG systems require. KIOXIA AiSAQ software makes it possible to meet these demands efficiently, enabling large-scale generative AI without being constrained by limited memory resources.

By open-sourcing KIOXIA AiSAQ software, the company is advancing SSD-centric architectures and supporting broader adoption of scalable AI systems.

“With the latest version of KIOXIA AiSAQ software, we’re giving developers and system architects the tools to fine-tune both performance and capacity,” said Neville Ichhaporia, senior vice president and general manager of the SSD business unit at KIOXIA America, Inc. “This level of flexibility is critical to building scalable, RAG systems – powered by SSD storage. By open-sourcing our technology, we’re reinforcing our commitment to the AI community with solutions that are both powerful and accessible to everyone."

Please follow the link to download KIOXIA AiSAQ open-source software: https://github.com/kioxia-jp/aisaq-diskann

For more information, please visit www.kioxia.com, and follow the company on X, formerly known as Twitter and LinkedIn^®.

About KIOXIA America, Inc.

KIOXIA America, Inc. is the U.S.-based subsidiary of KIOXIA Corporation, a leading worldwide supplier of flash memory and solid-state drives (SSDs). From the invention of flash memory to today’s breakthrough BiCS FLASH™ 3D technology, KIOXIA continues to pioneer innovative memory, SSD and software solutions that enrich people's lives and expand society's horizons. The company's innovative 3D flash memory technology, BiCS FLASH, is shaping the future of storage in high-density applications, including advanced smartphones, PCs, automotive systems, data centers and generative AI systems. For more information, please visit KIOXIA.com.

© 2025 KIOXIA America, Inc. All rights reserved. Information in this press release, including product pricing and specifications, content of services, and contact information is current and believed to be accurate on the date of the announcement, but is subject to change without prior notice. Technical and application information contained here is subject to the most recent applicable KIOXIA product specifications.

Notes:

KIOXIA AiSAQ: All-in-Storage ANNS with Product Quantization, a novel method of index data placement, is a trademark of KIOXIA.

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"This level of flexibility is critical to building scalable, RAG systems – powered by SSD storage. By open-sourcing our technology, we’re reinforcing our commitment to the AI community with solutions that are both powerful and accessible to everyone."