Software-defined storage market growth is fueled by accelerating unstructured data volumes, cloud-native adoption, AI-driven automation, and hybrid/multi-cloud deployments, with increasing uptake across North America and Asia-Pacific.

Hyderabad, India, Feb. 05, 2026 (GLOBE NEWSWIRE) — According to Mordor Intelligence, the software-defined storage market size reached USD 24.27 billion in 2026 and is projected to surge to USD 75.03 billion by 2031, expanding at a robust CAGR of 25.32% during the forecast period. This exceptional trajectory reflects accelerating enterprise demand for flexible, scalable, and hardware-agnostic storage architectures. 

The software-defined storage industry is gaining momentum as organizations shift away from traditional storage appliances toward software-centric platforms that decouple storage services from proprietary hardware. Growing adoption of cloud-native applications, virtualization, containerization, and data-intensive workloads such as AI and analytics is significantly contributing to the software-defined storage market growth across global enterprise environments. 

Software-Defined Storage Market Trends and Technology Shifts 

Managing the Surge of Unstructured Enterprise Data 
As digital activity accelerates, organizations are dealing with an overwhelming surge of unstructured data from sources such as video feeds, machine logs, and medical imaging. Legacy storage systems struggle to keep pace with this volume and complexity, driving enterprises toward software-defined storage modules market solutions built for scale and efficiency. These platforms allow data to be stored, accessed, and managed more flexibly, making them especially valuable for compliance-driven industries, AI-powered manufacturing workflows, and healthcare data retention. By shifting to software-defined architectures, organizations are improving performance, controlling storage costs, and simplifying long-term data governance. 

Smarter Storage Through AI-Driven Automation 
Artificial intelligence is increasingly shaping how modern storage systems operate. Software-defined platforms now use intelligent models to understand usage behavior, automatically moving rarely accessed data to lower-cost tiers while keeping frequently used information readily available. These systems can also anticipate performance issues and hardware risks, allowing storage environments to self-adjust without constant manual oversight. By adopting AI-driven storage solutions, companies are not only improving operational efficiency but also increasing their software-defined storage market share in data-heavy fields such as life sciences, where long-term storage management and active analysis demand highly optimized environments. 

Table of Contents (Partial) – Software-Defined Storage Industry 

1. INTRODUCTION 

  • 1.1 Study Assumptions and Market Definition 
  • 1.2 Scope of the Study 

2. RESEARCH METHODOLOGY 

3. EXECUTIVE SUMMARY 

4. MARKET LANDSCAPE 

  • 4.1 Market Overview 
  • 4.2 Market Drivers 
  • 4.2.1 Exponential Growth of Unstructured Enterprise Data 
  • 4.2.2 Cost-Advantaged Shift from Proprietary Arrays to Commodity Hardware 
  • 4.2.3 Hybrid/Multi-Cloud Adoption Demanding Storage Abstraction 
  • 4.2.4 AI/ML-Driven Autonomous Storage Management and Tiering 
  • 4.2.5 Container/Kubernetes-Native Persistent Storage Needs 
  • 4.2.6 and more 
  • 4.3 Market Restraints 
  • 4.3.1 Integration Complexity with Legacy Storage Estates 
  • 4.3.2 Shortage of Specialised SDS Skills and Organisational Change 
  • 4.3.3 Performance Determinism Concerns for Latency-Sensitive Apps 
  • 4.3.4 Fragmented Standards Increasing Vendor-Lock-In Risk 
  • 4.4 Indusy Value Chain Analysis 
  • 4.5 Regulatory Landscape 
  • 4.6 Technological Outlook 
  • 4.7 Porter’s Five Forces Analysis 
  • 4.7.1 Bargaining Power of Suppliers 
  • 4.7.2 Bargaining Power of Buyers 
  • 4.7.3 Threat of New Entrants 
  • 4.7.4 Threat of Substitutes 
  • 4.7.5 Intensity of Competitive Rivalry 

5. MARKET SIZE AND GROWTH FORECASTS (VALUE) 

  • 5.1 By Storage Type 
  • 5.1.1 Block 
  • 5.1.2 File 
  • 5.1.3 Object 
  • 5.1.4 Hyper-converged Infrastructure 
  • 5.2 By Deployment Mode 
  • 5.2.1 On-premises 
  • 5.2.2 Private Cloud 
  • 5.2.3 Public Cloud 
  • 5.2.4 Hybrid Cloud 
  • 5.3 By Organisation Size 
  • 5.3.1 Small and Medium Enterprises 
  • 5.3.2 Large Enterprises 
  • 5.4 By End-user Industry 
  • 5.4.1 Banking, Financial Services and Insurance (BFSI) 
  • 5.4.2 Telecom and Information Technology 
  • 5.4.3 Government and Public Sector 
  • 5.4.4 Healthcare and Life Sciences 
  • 5.4.5 and more 
  • 5.5 By Geography 
  • 5.5.1 North America 
  • 5.5.2 South America 
  • 5.5.3 Europe 
  • 5.5.4 Asia-Pacific 
  • 5.5.5 Middle East and Africa 
  • 5.5.5.1 Middle East 
  • 5.5.5.2 Africa 

6. COMPETITIVE LANDSCAPE 

  • 6.1 Market Concentration 
  • 6.2 Strategic Moves 
  • 6.3 Market Share Analysis 
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments) 
  • 6.4.1 Amazon Web Services, Inc. 
  • 6.4.2 Microsoft Corporation 
  • 6.4.3 International Business Machines Corporation 
  • 6.4.4 Dell Technologies Inc. 
  • 6.4.5 Hewlett-Packard Enterprise Company 
  • 6.4.6 NetApp, Inc.
  • 6.4.7 Huawei Technologies Co., Ltd. 
  • 6.4.8 Hitachi Vantara LLC 
  • 6.4.9 Pure Storage, Inc. 
  • 6.4.10 and more 

7. MARKET OPPORTUNITIES AND FUTURE OUTLOOK 

  • 7.1 White-space and Unmet-Need Assessment 

For details on other market segments and the full table of contents, visit – https://www.mordorintelligence.com/industry-reports/software-defined-storage-market?utm_source=globenewswire 

Software-Defined Storage Market Regional Outlook 

In North America, adoption of software-defined storage is being shaped by strong cloud infrastructure, early containerization practices, and strict regulatory requirements. Enterprises and public-sector organizations are increasingly favoring flexible storage architectures that support hybrid environments, allowing sensitive data to remain local while advanced analytics and applications run in the cloud. 

Across the Asia-Pacific region, rapid digitalization and expanding cloud ecosystems are driving widespread uptake of software-defined storage market solutions. Governments and enterprises are prioritizing scalable, policy-driven storage models to support high transaction volumes, edge deployments, and national data sovereignty requirements as digital services continue to expand. 

Related Reports by Mordor Intelligence 

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Autonomous Data Platform Market Growth: The autonomous data platform market is projected to grow from USD 2.13 billion in 2025 to USD 2.55 billion in 2026 and reach USD 6.27 billion by 2031, at a CAGR of 19.72% during the forecast period. This growth is driven by increasing reliance on AI and machine learning, the need to reduce manual data management workloads, growing adoption of cloud-native databases, and enterprise demand for self-optimizing, self-securing, and self-healing data platforms that enhance operational efficiency and scalability. 

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