2025年-2035年新兴存储器和存储技术：市场、趋势、预测
10年详细预测及市场规模评估——本报告涉及HBM、QLC固态硬盘、下一代硬盘（HAMR、MAMR）以及用于AI、HPC、数据中心、云、边缘、物联网和嵌入式应用程序的新兴存储器（MRAM、RRAM、FeRAM、PCM）的发展。
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本报告对存储器及存储市场、相关技术以及主要参与者进行了全面深入的分析。报告涵盖了HDD、SSD/NAND和DRAM这三大主要应用领域，并具体探讨了它们在AI/HPC（人工智能/高性能计算）、数据中心/云以及边缘计算中的应用。分析内容既包括2018年至2024年的历史市场数据，也涵盖了2025年至2035年的市场预测。此外，本报告还探讨了MRAM、ReRAM、FeRAM和PCM等新兴存储器技术，详细介绍了这些技术的市场潜力及采用趋势。随着全球存储器和存储市场预计到2035年将超过3000亿美元，本报告着重强调了塑造该行业未来的关键机遇。
该报告提供了当前存储器与存储市场及其主要应用领域的关键市场情报。报告重点介绍了主流商业技术，同时探讨了新兴存储器与存储解决方案及其当前和未来的应用。其中包括：
存储器与存储行业背景与技术回顾：
- 存储器技术的历史与背景
- 关键技术的总体概述
- 影响行业的趋势与主题
- 不同技术的基准测试与分析
每种主要技术的完整市场特征：
- 回顾当前主流存储和内存技术（HDD、SSD、DRAM），包括历史背景、HBM和QLC SSD的兴起
- 回顾新兴内存技术，包括历史背景、主要市场参与者以及MRAM、ReRAM、FeRAM和PCM的前景
全面的市场分析：
- 分析领先的内存和存储参与者，对60多家公司进行深入分析
- 2018年至2024年的历史市场数据
- 2024年至2035年HDD、SSD和DRAM在三个关键应用中的市场预测：AI/HPC、云/数据中心和边缘
- 计算，包括完整的叙述、限制和方法
1.执行摘要
2.引言
3.预测
- 硬盘驱动器按应用（云/数据中心和边缘）划分的规模
- SSD和NAND按应用（AI/HPC、云/数据中心和边缘）划分的规模
- 存储云/数据中心市场的规模
- 存储边缘市场的规模
- 内存按应用（AI/HPC、云/数据中心和边缘）划分的规模
- 高带宽存储器（HBM）的市场规模和年销量
- 服务器内存和存储器的市场规模
- 按应用（AI/HPC、云/数据中心和边缘）和类型（HDD、SSD/NAND和DRAM）划分的内存和存储器市场规模
- 按类型（ReRAM、MRAM、FeRAM和PCM）划分的内存市场规模
4. 存储
- 主要趋势
- 硬盘（HDD）
- 固态硬盘（SSD）
- 数据库对比 - QLC SSD和HDD
- 现有技术的改进
5. 内存
- 主要趋势
- 概述
- 双倍数据速率（DDR）内存
- 高带宽内存（HBM）
- 内存扩展
6. 新兴存储和内存
- 本报告涵盖的趋势和新兴技术
- 磁阻式RAM（MRAM）
- 电阻式RAM（ReRAM）
- 铁电RAM（FeRAM）
- 相变存储器（PCM）
- 新兴存储器平台对比
The explosion of AI and HPC workloads, the rising demand for data centers and cloud storage, and the expansion of IoT and edge computing are driving the need for next-generation memory and storage solutions, as well as the adoption of emerging memory technologies. IDTechEx's report, "Emerging Memory and Storage Technology 2025-2035: Markets, Trends, Forecasts", examines key technologies shaping the future of memory and storage, including SSDs (SLC, TLC, and QLC), HDDs, and emerging memory solutions such as Magnetoresistive RAM (MRAM), Resistive RAM (ReRAM/RRAM), Ferroelectric RAM (FeRAM), and Phase-Change Memory (PCM). The report also analyzes current and emerging market trends, provides an outlook for each technology, and highlights new commercial opportunities. A 10-year market size forecast for Hard Drive Disk Market (HDD), segmented by Application Datacentres/Cloud and Edge Applications.
Key Market Forecasts Covered in the Report:
- A 10-year market size forecast for Solid State Drives (SSD) / NAND Market, segmented by Application Artificial Intelligence / High Performance Computing (AI/HPC), Datacentres/Cloud and Edge Applications.
- A 10-year market size forecast for the Cloud/Datacentre Storage Market, segmented by HDD, SSD/NAND
- A 10-year market size forecast for Edge Storage Market, segmented by HDD, SSD/NAND
- A 10-year market size forecast for Yearly Unit Sales and Market Size of High Bandwidth Memory (HBM).
- A 10-year market size forecast for Memory and Storage for Servers for AI/HPC.
- A 10-year market size forecast for Dynamic Random Access Memory (DRAM) Market, segmented by AI/HPC, Datacentres/Cloud and Edge Applications.
- A 10-year market size forecast for Memory and Storage Market, segmented by HDD, SSD/NAND and DRAM
- A 10-year market size forecast for Memory and Storage Market, broken down by application AI/HPC Datacentres/Cloud and Edge Applications.
- A 10-year market size forecast for Emerging Memory Technologies, segmented by technology; Resistive RAM (ReRAM), Magnetoresistive RAM (MRAM), Ferroelectric RAM (FeRAM), Phase Change Memory (PCM).
Key Trends in Memory and Storage
The current memory and storage market is built on three dominant technologies: HDDs, SSDs, and DRAM. SSDs are increasingly replacing HDDs in many applications due to their higher performance and lower latency. However, HDDs remain essential for high-capacity storage. The introduction of Quad-Level Cell (QLC) SSDs is reshaping storage hierarchies, offering the highest density of any SSD while outperforming HDDs in speed and endurance.
As AI and HPC workloads demand greater performance, studies show that switching from traditional tiered storage (TLC SSDs for hot data and HDDs for cold data) to QLC SSDs can significantly reduce costs. A 10PB QLC SSD-based storage system is estimated to provide US$30.3 million in savings over 10 years, with a 47% reduction in total cost of ownership (TCO) over five years due to lower rack space, power consumption, and maintenance costs. This shift is particularly relevant for AI, HPC, and cloud applications, which rely on high-speed, high-density storage.
AI/HPC workloads require high bandwidth for parallel processing applications but face challenges due to memory bottlenecks—known as the memory wall—caused by processor advancements outpacing memory bandwidth. For example, large language models (LLMs) used in generative AI often experience less than 50% of peak processor performance due to these constraints. Solutions such as High Bandwidth Memory (HBM), which vertically stacks DRAM chips, are being adopted to increase data throughput. Emerging non-volatile memory (NVM) solutions, such as MRAM, are also being explored for storage-class memory (SCM) applications.
In embedded memory applications, NOR Flash currently dominates, but it faces limitations in performance, endurance, and scalability. NOR Flash struggles to scale below 28nm, making it incompatible with advanced CMOS processes for microcontroller (MCU) manufacturing. This has created an opportunity for emerging NVM solutions like ReRAM and MRAM, which can scale below 10nm. Companies like Everspin have already gained traction in this space, while major players such as TSMC, GlobalFoundries, and Samsung are integrating emerging NVM into their platforms.
IDTechEx's report "Emerging Memory and Storage Technology 2025-2035: Markets, Trends, Forecasts" projects that the market size for memory and storage technologies will double, with emerging memory technologies expected to grow 2.2 times their current size over this period.
Memory and Storage Market by Application. For full data, refer to "Emerging Memory and Storage Technology 2025-2035: Markets, Trends, Forecasts". Source: IDTechEx
Emerging Memory Market by Technology. For full data, refer to "Emerging Memory and Storage Technology 2025-2035: Markets, Trends, Forecasts". Source: IDTechEx
For those looking to understand the evolving memory and storage landscape, including key trends, emerging technologies, and market outlooks, IDTechEx's report provides a detailed assessment of the industry's future. The growth of AI/HPC, cloud storage, and edge computing is driving demand for high-capacity, high-performance storage and low power, next-generation and emerging memory solutions.
As such, "Emerging Memory and Storage Technology 2025-2035: Markets, Trends, Forecasts" provides comprehensive 10-year forecasts not only for the overall memory and storage market but also for key hardware technologies, including HDDs, SSDs, and DRAM, as well as major application areas. In addition, it provides forecasts for the emerging memory sector, covering key technologies such as MRAM, ReRAM, FeRAM, and PCM. Readers will gain a deep understanding of the present and future of the industry, equipping them with the insights needed to make informed strategic decisions.
Key Aspects
This report provides critical market intelligence on the current memory and storage market and its key application sectors. It highlights the dominant commercial technologies while exploring emerging memory and storage solutions and their current and future applications. This includes:
A Review of the Context and Technology within the Memory & Storage Industry:
- History and context of memory technologies
- General overview of key technologies
- Trends and themes shaping the industry
- Benchmarking and analysis of different technologies
Full Market Characterization for Each Major Technology:
- Review of the current dominant storage and memory landscape (HDD, SSD, DRAM), including historical context, the rise of HBM & QLC SSDs
- Review of emerging memory technologies, covering historical context, key market players, and outlook for MRAM, ReRAM, FeRAM, and PCM
Comprehensive Market Analysis:
- Analysis of leading memory and storage players, with insights from over 60 companies
- Historical market data from 2018 to 2024
- Market forecasts from 2024 to 2035 for HDDs, SSDs, and DRAM across three key applications: AI/HPC, Cloud/Data Centers, and Edge
- Computing, including full narrative, limitations, and methodologies
| Report Metrics | Details |
|---|---|
| Historic Data | 2018 - 2024 |
| CAGR | The global market of Memory & Storage will grow at a CAGR of 9% between 2024 and 2035 |
| Forecast Period | 2024 - 2035 |
| Forecast Units | Market Size (Revenue) (US$Billion) |
| Regions Covered | Worldwide |
| Segments Covered | Memory and Storage technologies: - Hard Drive Disks (HDDs) - Solid State Drives (SSDs) Memory: - Static Random Access Memory (SRAM) - Dynamic Random Access Memory (DRAM) - High Bandwidth Memory (HBM) - Double Data Rate (DDR) Emerging Technologies: - Magnetoresistive RAM (MRAM) - Resistive RAM (ReRAM / RRAM) - Ferroelectric RAM (FeRAM / FRAM) - Phase Change Memory (PCM / PCRAM) Applications Covered: - AI / HPC - Datacentres / Cloud - Edge |
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| 1. | EXECUTIVE SUMMARY |
| 1.1. | The Impact of Data Growth and Energy Consumption |
| 1.2. | Modern Applications are Demanding High Performance Storage |
| 1.3. | Memory bottlenecks for High Performance workloads |
| 1.4. | Hierarchy of computing memory |
| 1.5. | What are HDDs? How Do They Work? |
| 1.6. | Hard Disk Drive Market in 2024 |
| 1.7. | Forecast: Hard Disk Drive by Application |
| 1.8. | SSDs Cell Types |
| 1.9. | Key Manufactures of SSDs and Market Size |
| 1.10. | Evolution of Capacity in QLC SSDs & HDDs |
| 1.11. | Capacity Density Comparison of QLC SSDs & HDDs |
| 1.12. | QLC SSDs & HDDs Best Metric Comparison Table |
| 1.13. | Forecast: SSDs & NAND by Application |
| 1.14. | What is DRAM? |
| 1.15. | HBM |
| 1.16. | Forecast: Yearly Unit Sales and Market Size of High Bandwidth Memory (HBM) |
| 1.17. | Forecast: Memory by Application |
| 1.18. | Emerging memory technologies: PCRAM, FRAM, RRAM, MRAM. |
| 1.19. | Emerging Non-Volatile Memory Technology |
| 1.20. | Companies involved within the Emerging Memory Space |
| 1.21. | Emerging Memory is Taking the Embedded Route |
| 1.22. | Emerging Memory Still Has a Path to Viability as Storage-Class Memory |
| 1.23. | Forecast: Market size of Emerging Memory by Type |
| 1.24. | IDTechEx Analysis: Future Outlook for MRAM |
| 1.25. | IDTechEx Analysis: Future Outlook for ReRAM |
| 1.26. | IDTechEx insight: Commercial FeRAM should adopt HfO₂ to move out of niche |
| 1.27. | IDTechEx Outlook & Comments for FeRAM |
| 1.28. | Failure of PCM as Storage Class Memory (2015-2023) |
| 1.29. | IDTechEx Outlook & Comments for PCM |
| 1.30. | Memory and Storage Technology Readiness Level |
| 1.31. | Access More With an IDTechEx Subscription |
| 2. | INTRODUCTION |
| 2.1.1. | Understanding the Memory Hierarchy for General Computing |
| 2.1.2. | Trends for storage and memory in Todays tech climate |
| 2.2. | AI & HPC |
| 2.2.1. | HPC - overview |
| 2.2.2. | AI as a Leading Driver for Memory solutions |
| 2.2.3. | Data movement through storage tiers in clusters for AI workloads |
| 2.2.4. | Modern Applications are Demanding High Performance Storage |
| 2.2.5. | Memory bottlenecks for High Performance workloads |
| 2.2.6. | Overview of trends in HPC chip integration |
| 2.3. | Cloud Storage |
| 2.3.1. | The Impact of Data Growth and Energy Consumption |
| 2.3.2. | Rising Data Storage Costs |
| 2.3.3. | On-premises, cloud, and hybrid storage solutions: Shift towards cloud & hybrid |
| 2.4. | Embedded Memory |
| 2.4.1. | What are Embedded Memory and Embedded Systems? |
| 2.4.2. | Types of Embedded Memory |
| 2.4.3. | Embedded Flash Struggles with sub-28nm |
| 2.4.4. | Scaling Embedded Memory to Advanced Nodes is Important for Key Metrics |
| 2.5. | Edge Devices & IoT |
| 2.5.1. | Edge Devices also is a Driver for Memory Solutions |
| 2.5.2. | Edge vs Cloud characteristics |
| 2.5.3. | Embedded Memory in Automotive Vehicles |
| 2.5.4. | Edge AI in Smart Appliances |
| 3. | FORECASTS |
| 3.1. | Forecast Methodology |
| 3.2. | Forecast: Market size of Hard-Drive-Disk by Application |
| 3.3. | Forecast: SSDs & NAND by Application |
| 3.4. | Forecast: Market size of Storage Cloud/Data Center Market |
| 3.5. | Forecast: Market size of Storage Edge Market |
| 3.6. | Forecast: Memory by Application |
| 3.7. | Forecast: Yearly Unit Sales and Market Size of High Bandwidth Memory (HBM) |
| 3.8. | Forecasts: Memory and Storage for Servers for AI/HPC |
| 3.9. | Forecast: Memory & Storage Market by Application & Type |
| 3.10. | Forecast: Top Level Forecast Memory & Storage Market |
| 3.11. | Forecast: Market size of Emerging Memory by Type |
| 4. | STORAGE |
| 4.1. | Overview |
| 4.1.1. | The Impact of Data Growth and Energy Consumption |
| 4.1.2. | Rising Data Storage Costs |
| 4.1.3. | Modern Applications are Demanding High Performance |
| 4.1.4. | Trends for Storage in Todays Tech Climate |
| 4.1.5. | Understanding the Memory Hierarchy for General Computing |
| 4.1.6. | Storage in Datacentres |
| 4.1.7. | Flash storage is the leading storage technology for HPC and AI applications |
| 4.1.8. | HPC and AI require large-scale and high-performance data storage |
| 4.1.9. | Storage requirements varies depending on the AI workloads |
| 4.1.10. | Data movement through storage tiers in clusters for AI workloads |
| 4.1.11. | Example of SSD configurations and solutions for AI and HPC workloads |
| 4.1.12. | Examples of SK Hynix NAND Flash storage for AI and data centers |
| 4.1.13. | Solidigm (SK Hynix subsidiary) offers SSDs previously manufactured by Intel |
| 4.1.14. | Micron has a range of SSDs for applications in datacenters and AI |
| 4.1.15. | Micron's 9550 SSDs are designed for AI-critical workloads with PCIe Gen5 |
| 4.1.16. | KIOXIA offers a range of datacenter and enterprise SSD solutions |
| 4.1.17. | Storage in Edge Computing Devices |
| 4.2. | Hard Drive Disks (HDDs) |
| 4.2.1. | What are HDDs? How Do They Work? |
| 4.2.2. | Advancements in HDD Technology |
| 4.2.3. | Energy-Assisted Magnetic Recording (EAMR) Technologies |
| 4.2.4. | Data Centre HDD match up |
| 4.2.5. | Benefits and Drawbacks to HDDs relative to QLC SSDs |
| 4.2.6. | Hard Disk Drive Market in 2024 |
| 4.2.7. | HDDs Market Historically |
| 4.3. | Solid State Drives (SSDs) |
| 4.3.1. | What are SSDs? How Do They Work? |
| 4.3.2. | NAND Flash memory uses floating gates or charge traps to store data |
| 4.3.3. | Advancements in SSD Technology |
| 4.3.4. | NAND Layer Stacking |
| 4.3.5. | SK Hynix - NAND technology development |
| 4.3.6. | SK Hynix: Overcoming stacking limitations to increase capacity using 4D2.0 |
| 4.3.7. | KIOXIA uses BiCS 3D FLASHTM Technology to increase storage density |
| 4.3.8. | SSDs Cell Types |
| 4.3.9. | SLC SSDs |
| 4.3.10. | SSDs for storage class memory bridging gap to volatile memory |
| 4.3.11. | TLC SSDs |
| 4.3.12. | QLC SSDs |
| 4.3.13. | Increasing SSD capacity through emerging lower cost QLC NAND |
| 4.3.14. | QLC affords higher capacity at a lower cost per bit but with performance deficits |
| 4.3.15. | Benefits and Drawbacks to QLC SSDs |
| 4.3.16. | Use Cases of HDDs & QLC SSDs |
| 4.3.17. | Data center and enterprise SSD form factors transitioning towards EDSFF |
| 4.3.18. | Step change in sequential read bandwidth with each generation of PCIe |
| 4.3.19. | Evolution of PCIe generations in the SSD market |
| 4.3.20. | Key Manufactures of SSDs and Market Size |
| 4.3.21. | SSD Market Historically |
| 4.3.22. | Storage Market |
| 4.4. | Database Comparison - QLC SSD & HDD |
| 4.4.1. | Why Compare QLC SSDs & HDDs |
| 4.4.2. | Important KPI's for Comparison |
| 4.4.3. | Evolution of Capacity of QLC SSDs & HDDs |
| 4.4.4. | Capacity Density Comparison of QLC SSDs & HDDs |
| 4.4.5. | Sequential Bandwidth of QLC SSDs & HDDs |
| 4.4.6. | Capacity-to-Power Ratio of QLC SSDs & HDDs |
| 4.4.7. | Capacity Density / Power of QLC SSDs & HDDs |
| 4.4.8. | Capacity Density / Power of QLC SSDs & HDDs |
| 4.4.9. | QLC SSDs & HDDs Best Metric Comparison Table |
| 4.5. | Going Forward - Improving Current Technologies |
| 4.5.1. | SK Hynix Unveils Penta-Level 3D NAND Flash Memory in 2024 |
| 4.5.2. | Macronix Introduced Compute-In-Memory 3D NOR Flash technology for AI Applications in 2024 |
| 4.5.3. | SK Hynix introduced Accelerator-in-Memory for LLM Inference |
| 5. | MEMORY |
| 5.1. | Overview |
| 5.1.1. | Hierarchy of computing memory |
| 5.1.2. | Memory bottlenecks for HPC/AI workloads and processor under-utilization |
| 5.1.3. | What is DRAM? |
| 5.1.4. | What is SRAM? |
| 5.1.5. | Types of DRAM and Comparison of HBM with DDR |
| 5.1.6. | HBM vs DDR for computing - market trend |
| 5.2. | DDR Memory |
| 5.2.1. | Developments in double data rate (DDR) memory |
| 5.2.2. | DDR5 memory in AMD's 4th Gen EPYC processors for HPC workloads |
| 5.2.3. | DDR5 MRDIMM increases capacity and bandwidth for high CPU core counts |
| 5.2.4. | NVIDIA's Grace CPU uses LPDDR5X memory to lower power consumption |
| 5.2.5. | GDDR7 announced by major players targeting HPC and AI applications |
| 5.2.6. | Comparison of GDDR6 and GDDR7 modules |
| 5.3. | High Bandwidth Memory (HBM) |
| 5.3.1. | HBM |
| 5.3.2. | High bandwidth memory (HBM) and comparison with other DRAM technologies |
| 5.3.3. | Demand outgrows supply for HBM in 2024 |
| 5.3.4. | HBM (High Bandwidth Memory) packaging |
| 5.3.5. | HBM packaging transition to hybrid bonding |
| 5.3.6. | Benchmark of HBM performance utilizing µ bump and hybrid bonding |
| 5.3.7. | SK Hynix has started volume production of 12-layer HBM3E |
| 5.3.8. | Micron released 24GB HBM3E for NVIDIA H200 and is sampling 36GB HBM3E |
| 5.3.9. | Samsung expects production of HBM3E 36GB within 2024 |
| 5.3.10. | Overview of current HBM stacking technologies by 3 main players |
| 5.3.11. | Evolution of HBM generations and transition to HBM4 |
| 5.3.12. | Benchmarking of HBM technologies in the market from key players (1) |
| 5.3.13. | Benchmarking of HBM technologies in the market from key players (2) |
| 5.3.14. | Examples of CPUs and accelerators using HBM |
| 5.3.15. | Intel's CPU Max series for HPC workloads has HBM and optional DDR |
| 5.3.16. | AMD CDNA 3 APU architecture with unified HBM memory for HPC |
| 5.3.17. | Three main approaches to package HBM and GPU |
| 5.3.18. | Drawbacks of High Bandwidth Memory (HBM) |
| 5.4. | Memory Expansion |
| 5.4.1. | Samsung's CMM-D memory expansion for AI and datacenter server applications |
| 5.4.2. | Micron's CXL memory expansion modules for storage tiering in datacenters |
| 5.4.3. | Memory Market |
| 5.4.4. | DDR memory dominates CPUs whereas HBM is key to GPU performance |
| 5.5. | Memory Market |
| 5.5.1. | DDR memory dominates CPUs whereas HBM is key to GPU performance |
| 5.5.2. | Memory market |
| 6. | EMERGING STORAGE & MEMORY |
| 6.1. | Overview |
| 6.1.1. | Memory bottlenecks for HPC/AI workloads and processor under-utilization |
| 6.1.2. | Embedded Flash Struggles with sub-28nm |
| 6.1.3. | Scaling Embedded Memory to Advanced Nodes is Important for Key Metrics |
| 6.1.4. | Emerging memory technologies: PCRAM, FRAM, RRAM, MRAM. |
| 6.2. | Magnetoresistive RAM (MRAM) |
| 6.2.1. | What is Magnetoresistive RAM (MRAM)? How Does it Work? |
| 6.2.2. | Types of (MRAM) |
| 6.2.3. | Benefits and Drawbacks to MRAM |
| 6.2.4. | Current Applications of MRAM |
| 6.2.5. | MRAM Specific Companies & Startups |
| 6.2.6. | MRAM Specific Companies & Startups |
| 6.2.7. | Everspin Technologies is the leading supplier of discrete MRAM components |
| 6.2.8. | Everspin xSPI STT-MRAM sets new benchmark MRAM |
| 6.2.9. | Everspin Expands MRAM Portfolio for Edge AI and Embedded Systems |
| 6.2.10. | Everspin Target Markets is Growing With New applications |
| 6.2.11. | Avalanche Technology's MRAM Adoption in Aerospace Applications |
| 6.2.12. | TSMC's Involvement in MRAM |
| 6.2.13. | TSMC and NXP MRAM in Automotive Industry |
| 6.2.14. | TSMC: STT-MRAM Co-Optimized for AI Edge Devices |
| 6.2.15. | Samsung's Role in MRAM Research and Development |
| 6.2.16. | Samsung Unveils World Most Write Energy 14nm eMRAM Technology for Automotive Applications |
| 6.2.17. | Samsung Reveals Smallest-Cell eMRAM Compatible With 8nm Logic Node for Automotive Applications |
| 6.2.18. | Netsol Uses Samsung Foundry 28nm Process to produce MRAM Products |
| 6.2.19. | Kioxia Introduces World Smallest 1Selector-1MTJ Cell for 64 Gb Cross-Point MRAM |
| 6.2.20. | MRAM Market: Segmentation by Company Type |
| 6.2.21. | IDTechEx Analysis: Future Outlook for MRAM |
| 6.3. | Resistive RAM (ReRAM) |
| 6.3.1. | What is Resistive Ram (ReRAM)? How Does it Work? |
| 6.3.2. | Benefits and Drawbacks to ReRAM |
| 6.3.3. | Current Applications of ReRAM |
| 6.3.4. | ReRAM Market: Segmentation by Company Type |
| 6.3.5. | ReRAM Market Historically |
| 6.3.6. | ReRAM Specific Companies & Startups |
| 6.3.7. | ReRAM Specific Companies & Startups |
| 6.3.8. | Weebit Nano Developing and Licensing ReRAM Technology |
| 6.3.9. | Weebit Nano's Roadmap for ReRAM in AI Applications |
| 6.3.10. | CrossBar Inc Licensing ReRAM Technology |
| 6.3.11. | CrossBar Inc Provides High Performance Embedded and 3D High Density ReRAM |
| 6.3.12. | 4DS Memory Develops Area Based Interface Switching ReRAM |
| 6.3.13. | RAMXEED ReRAM Technology and Development |
| 6.3.14. | GlobalFoundries Demonstrates ReRAM in its 22FDX Platform |
| 6.3.15. | TSMC integrates ReRAM into its nRF54L Series SoCs AT 22nm |
| 6.3.16. | IDTechEx Analysis: Future Outlook for ReRAM |
| 6.4. | Ferroelectric RAM (FeRAM) |
| 6.4.1. | What is Ferroelectric RAM (FeRAM)? How Does it Work? |
| 6.4.2. | Benefits and Drawbacks to FeRAM |
| 6.4.3. | Current Applications of FeRAM |
| 6.4.4. | FeRAM Market: Segmentation by Company Type |
| 6.4.5. | RAMXEED FeRAM Technology and Development |
| 6.4.6. | Infineon is a leading supplier of FeRAM |
| 6.4.7. | Micron FeRAM Achieves Industry-Leading Density |
| 6.4.8. | Ferroelectric Memory Company Targets HfO2 FeRAM Commercialization |
| 6.4.9. | SK Hynix Unveils Ultra-High-Density 3D FeNAND Arrays for Analog Computation of Hyperscale AI Models |
| 6.4.10. | TSMC Showcases Ferroelectric FET Memory with Smallest Cell Area and High Endurance |
| 6.4.11. | IDTechEx Insight - Commercial FeRAM Needs HfO₂ to Stay Competitive |
| 6.4.12. | IDTechEx Outlook & Comments for FeRAM |
| 6.5. | Phase Change Memory (PCM) |
| 6.5.1. | What is Phase Change Memory (PCM/PCRAM) How Does it Work? |
| 6.5.2. | Benefits and Drawbacks to PCM |
| 6.5.3. | PCM Market: Segmentation by Company Type |
| 6.5.4. | PCM Market Lessons from Intel Optane Failure |
| 6.5.5. | Micron 3DXPoint |
| 6.5.6. | Failure of PCM as Storage Class Memory (2015-2023) |
| 6.5.7. | STMicroelectronics produces ePCM for Microcontrollers in automotive controllers |
| 6.5.8. | STMicroelectronics presents Single-Ended ePCM Memory Array for Neural Network Weight Storage in Edge-AI Applications |
| 6.5.9. | PCM Market |
| 6.5.10. | IDTechEx Outlook & Comments for PCM |
| 6.6. | Comparison of Emerging Memory Platforms |
| 6.6.1. | Emerging Memory Still Has a Path to Viability as Storage-Class Memory |
| 6.6.2. | Emerging Memory is Taking the Embedded Route |
| 6.6.3. | Comparison of Emerging Technology |
| 6.6.4. | IDTechEx Comparison of Commercialized Emerging Tech Products |
| 6.6.5. | Companies involved within the Emerging Memory Space |
| 7. | COMPANY PROFILES |
| 7.1. | Company Profiles Included with this Report |
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2025年-2035年新兴存储器和存储技术：市场、趋势、预测
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到2035年，存储器和存储市场的年市场规模将超过3000亿美元
报告统计信息
| 幻灯片 | 256 |
|---|---|
| 预测 | 2035 |
| 已发表 | Apr 2025 |
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