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Computational Storage Market Value Growth And Long-Term Outlook
The computational storage market’s size has demonstrated exponential growth in recent years. It is anticipated to increase from $6.37 billion in 2025 to $7.84 billion in 2026, exhibiting a compound annual growth rate (CAGR) of 23.0%. The historical period’s growth can be ascribed to a combination of factors such as escalating enterprise data volumes, an increased demand for expedited data processing, the expanding implementation of high-performance computing infrastructure, the growing burden on centralized computing resources, and a heightened requirement for proficient data management.
The computational storage market size is projected to experience substantial growth in the upcoming period. This market is expected to reach $17.71 billion in 2030, demonstrating a compound annual growth rate (CAGR) of 22.6%. The expansion during the forecast period is primarily driven by the escalating demand for real-time data processing, the increasing adoption of data-intensive applications, a rising need for infrastructure resource optimization, the expanding requirement for storage-level analytics, and the growing demand for low-latency computing architectures. Prominent trends observed in this forecast period include the increasing incorporation of data processing directly within storage devices, a heightened demand for reduced data movement, a growing preference for low-latency data processing, the continuous integration of computational capabilities into storage infrastructure, and the expanding utilization of storage-level data filtering and compression.
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Computational Storage Market Demand Drivers Opening New Revenue Streams
The projected expansion of the computational storage market is significantly influenced by the dramatic surge in enterprise data volumes. This refers to the fast-growing quantities of both structured and unstructured data that organizations create, retain, and process via diverse channels such as applications, business operations, IoT devices, analytics platforms, and digital services. The primary reason for this increase is the wider adoption of digital applications, which produce substantial volumes of structured and unstructured data, demanding effective solutions for storage, management, and processing. As enterprise data volumes continue their exponential rise across various sectors, there is a compelling need for sophisticated data processing architectures. In this context, Computational Storage allows organizations to bypass conventional storage limitations by integrating computation directly with data, thereby boosting performance, minimizing data transfers, improving scalability, and streamlining the efficiency of enterprise workloads. Illustratively, in March 2024, the US-based software company Edge Delta reported that an estimated 120 zettabytes (ZB) of data were generated globally, equating to approximately 337,080 petabytes (PB) daily. Considering the approximately 5.35 billion internet users worldwide, this implies that, on average, each user might be generating around 15.87 terabytes (TB) of data daily. Consequently, the significant proliferation of enterprise data volumes is a key impetus for the expansion of the computational storage market.
Computational Storage Market Segment Performance And Emerging Opportunities
The computational storage market covered in this report is segmented –
1) By Component: Hardware, Software, Services
2) By Storage Type: Solid State Drive, Hard Disk Drive, Hybrid
3) By Deployment Mode: On-Premises, Cloud
4) By Application: Data Centers, Edge Computing, Cloud Computing, Enterprise Storage, Other Applications
5) By End User: Information Technology And Telecommunications, Banking, Financial Services, And Insurance, Healthcare, Government, Media And Entertainment, Other End Users
Subsegments:
1) By Hardware: Computational Storage Drives, Solid State Drives With Computational Capabilities, Storage Processing Units, Computational Storage Controllers
2) By Software: Computational Storage Management Software, Data Processing And Analytics Software, Storage Virtualization Software, Application Programming Interface Based Computational Storage Software
3) By Services: Implementation And Integration Services, Consulting And Advisory Services, Maintenance And Support Services, Managed Computational Storage Services
Computational Storage Market Trends Powering Strategic Industry Growth
Leading companies operating within the computational storage market are directing their efforts toward developing innovative technologies, particularly high-speed interface-based computational storage solutions. These advancements aim to enhance data processing efficiency, minimize latency, optimize storage performance, and effectively support data-intensive workloads such as artificial intelligence (AI), databases, and cloud computing applications. High-speed interface-based computational storage solutions are sophisticated storage technologies that integrate computational capabilities directly into storage devices, allowing data to be processed at the storage layer itself rather than requiring large datasets to be transferred to external processors. This approach reduces data movement, improves response times, and results in lower overall infrastructure costs compared with traditional storage architectures. For example, in January 2024, NVM Express, Inc., a US-based non-profit organization, introduced the NVM Express Computational Storage Feature Specification, an industry-standard framework crafted to enable communication between applications and NVMe computational storage devices across both compute and storage environments. The specification outlines two primary command sets: the Computational Programs Command Set, which facilitates a host-driven and modular method for deploying computational programs onto storage devices, and the Subsystem Local Memory Command Set, which permits access to memory within an NVMe subsystem through computational programs and NVMe I/O commands. These features empower enterprises and hyperscale data centers to offload compute-intensive operations directly to storage devices, thereby improving performance for latency-sensitive applications including AI models, databases, and content delivery networks. This significant advancement underscores the increasing adoption of standardized computational storage technologies to enhance scalability, interoperability, and efficiency in modern data-intensive computing environments.
Computational Storage Market Key Players Shaping Industry Direction
Major companies operating in the computational storage market are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, NVIDIA Corporation, Intel Corporation, IBM Corporation, Dell Technologies Inc., Hewlett Packard Enterprise Company, Broadcom Inc., Advanced Micro Devices Inc., Western Digital Corporation, Micron Technology Inc., NetApp Inc., Samsung Electronics Co. Ltd., Pure Storage Inc., Seagate Technology Holdings plc, SK hynix Inc., Marvell Technology Inc., KIOXIA Holdings Corporation, ScaleFlux Inc., Eideticom Inc.
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Computational Storage Market Regional Analysis: Which Geography Leads On Revenue?
North America was the largest region in the computational storage market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the computational storage market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.