US and Hong Kong Storage Industry
Explore the US and Hong Kong storage industry, including the growing demand created by artificial intelligence, cloud computing, and data centers. This topic covers HBM, DRAM, NAND, SSD, HDD, and related technologies, along with the products, financial performance, industry cycles, competition, and valuations of relevant US- and Hong Kong-listed companies. Company analysis, earnings coverage, and industry guides help readers understand the storage supply chain, its major participants, and the opportunities and risks associated with the sector.
Related Blogs
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Memory chip stocks and enterprise storage system stocks do not follow the same investment logic. The former are mainly affected by DRAM, NAND, and HBM pricing and supply-demand cycles, while the latter depend more on enterprise IT budgets, storage arrays, software subscriptions, and data management services. Investors should compare them through business models, profit sources, cyclical attributes, and AI data center demand.
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2026-06-29 16:21:37
How to Read the Inventory Cycle of Memory Stocks? Inventory, Customer Restocking, and Price Inflection Signals
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How Should SSDs and HDDs Work Together in AI Data Centers? Performance, Capacity, Cost, and Hot vs. Cold Data Compared
AI data centers are not only about GPUs. The way SSDs and HDDs are divided across training, inference, data lakes, backup, and archive layers affects performance and cost. This guide compares SSDs and HDDs in AI data centers across latency, capacity, TCO, energy use, rack density, and hot/cold data tiering.
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What Are NOR Flash, SLC NAND, and EEPROM? Why They Help Explain Hong Kong-Listed Memory-Related Stocks
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Why Does AI Compute Growth Drive Storage Demand? The Difference Between Training, Inference, and Data Retention
Why does AI compute growth drive storage demand? This article explains how HBM, DRAM, enterprise SSDs, nearline HDDs, object storage, and data center storage are affected by AI workloads across training, inference, and data retention.
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