The storage in big data market is expanding rapidly due to increasing volumes of enterprise and IoT data, growing adoption of cloud and software-defined storage solutions, and rising demand for AI-driven analytics and real-time data management, with the U.S. market projected to reach USD 88.01 billion by 2035.
Austin, May 11, 2026 (GLOBE NEWSWIRE) — The Storage in Big Data Market was valued at USD 66.18 billion in 2025 and is expected to reach USD 330.99 billion by 2035, growing at a CAGR of 17.57% from 2026 to 2035.
The need for scalable big data storage solutions is being accelerated by the growing amounts of structured and unstructured data from businesses, IoT devices, cloud platforms, and digital services. Cloud storage, software-defined storage, and sophisticated data management technologies are being used by organizations more frequently to enable analytics, artificial intelligence, and real-time decision-making.

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U.S. Storage in Big Data Market was valued at USD 18.09 billion in 2025 and is expected to reach USD 88.01 billion by 2035, growing at a CAGR of 17.14%.
Rapid growth in enterprise data volumes, expanding cloud adoption, and rising use of AI and analytics are driving demand for scalable storage. Increasing IoT deployment, regulatory data retention needs, and modernization of legacy infrastructure further support sustained market expansion.
Increasing Data Generation Across Enterprises Augment Market Growth Globally
The need for sophisticated storage solutions is fueled by the enormous growth of enterprise data from social media, IoT devices, and transactional systems. To store, manage, and retrieve massive amounts of unstructured, semi-structured, and structured data, organizations need reliable systems. To extract useful insights and streamline processes, big data analytics depends on safe, high-performance storage. For predictive analytics, customer insights, and operational efficiency, industries like BFSI, IT, manufacturing, and healthcare are using storage solutions more and more. The demand for storage in big data solutions is being driven by the increasing volume, variety, and velocity of data around the world, which is propelling market growth.
Segmentation Analysis:
By Deployment Mode
Cloud dominated with 61% share in 2025 and is also expected to grow with the fastest CAGR during the forecast period due to its flexibility, scalability, and cost-effectiveness, allowing enterprises to manage large volumes of structured and unstructured data efficiently.
By Component
Services dominated with 40% share in 2025 and is also projected to be the fastest growing segment during the projected period as enterprises increasingly rely on consulting, integration, deployment, and maintenance services to manage complex storage infrastructure.
By Storage Type
Cloud Storage dominated with 24% share in 2025 due to its scalability, flexibility, and cost-efficiency. Software-Defined Storage (SDS) segment is expected to grow at the fastest CAGR from 2026-2035 as organizations adopt SDS for flexibility, automation, and efficient management of heterogeneous storage environments.
By Industry
BFSI dominated with 26% share in 2025 due to the high demand for secure, real-time storage solutions for transactions, risk analysis, and fraud detection. Retail segment is expected to grow at the fastest CAGR from 2026-2035 as retailers increasingly use big data storage to analyze customer behavior, optimize inventory, and enhance personalized marketing.
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Regional Insights:
Due to early adoption of big data technologies, a strong presence of top cloud and storage providers, and significant expenditures in digital infrastructure, North America dominated the storage in big data market in 2025, with the greatest revenue share of over 38%. Advanced storage solutions are used by businesses in BFSI, IT, healthcare, and retail to handle massive amounts of data, analytics, and regulatory compliance.
Due to expanding cloud use, rapid digitalization, and rising enterprise data output in emerging nations, the Asia Pacific segment is predicted to grow at the quickest CAGR of almost 18.90% between 2026 and 2035. Big data analytics is being used more and more by sectors including telecom, manufacturing, retail, and BFSI.
Key Companies:
- IBM Corporation
- Dell Technologies Inc.
- Hewlett Packard Enterprise (HPE)
- NetApp, Inc.
- Amazon Web Services (AWS)
- Microsoft Corporation (Azure)
- Google LLC (Google Cloud)
- Oracle Corporation
- SAP SE
- SAS Institute Inc.
- Hitachi Vantara (Hitachi, Ltd.)
- Western Digital Corporation
- Seagate Technology PLC
- Huawei Technologies Co., Ltd.
- Samsung Electronics Co., Ltd.
- Pure Storage, Inc.
- Teradata Corporation
- VMware Inc.
- Scality
- Cloudian
Recent Developments:
2023: IBM launched Storage Scale System 6000, offering 7M IOPS and high bandwidth throughput for demanding AI and big data workloads.
2024: NetApp unveiled AFF A-Series for modern workloads, delivering high IOPS, scalable throughput, and enterprise-grade security for big data and AI pipelines.
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Exclusive Sections of the Report (The USPs):
- Big Data Storage Pricing & Cost Analysis – helps you understand storage cost trends across HDD, SSD, cloud, and hybrid solutions, including subscription-based, pay-per-use, and tiered pricing models adopted by enterprises globally.
- Regulatory & Data Compliance Insights – helps you evaluate the impact of GDPR, HIPAA, CCPA, and emerging data sovereignty regulations on cloud and on-premises storage deployments, security strategies, and enterprise compliance adoption.
- Storage Deployment & Capacity Utilization Metrics – helps you analyze deployment trends across cloud, hybrid, and on-premises infrastructure, storage utilization efficiency, data tiering adoption, and average enterprise data volume growth.
- Performance, Reliability & Backup Analysis – helps you uncover benchmarks related to IOPS performance, latency, throughput, system uptime, SLA compliance, backup adoption, and redundancy strategies across enterprise storage platforms.
- AI-Driven Storage Technology & Innovation Trends – helps you identify opportunities in AI/ML-enabled storage management, predictive maintenance, automated tiering, NVMe adoption, software-defined storage, object storage, and edge storage technologies.
- Competitive Landscape & Strategic Positioning – helps you gauge the competitive strength of leading storage solution providers based on pricing strategies, cloud capabilities, technology innovation, deployment scalability, and global market reach.
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