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Next-Generation Data Storage Market to Grow by USD 29.2 Billion from 2024-2028, Driven by IoT and Big Data Demand, AI-Powered Report- Technavio

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NEW YORK, Sept. 10, 2024 /PRNewswire/ — Report on how AI is driving market transformation- The global next-generation data storage market size is estimated to grow by USD 29.2 billion from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of 8.08% during the forecast period. Growing demand for iot and big data operations is driving market growth, with a trend towards software-defined storage. However, high operating expenses for vendors poses a challenge. Key market players include Cloudian Inc., DataDirect Networks Inc., Dell Technologies Inc., Drobo Inc., Furukawa Electric Co. Ltd., Hewlett Packard Enterprise Co., Hitachi Ltd., Inspur Group, International Business Machines Corp., Micron Technology Inc., NetApp Inc., Netgear Inc., Nutanix Inc., Oracle Corp., Pure Storage Inc., Quantum Corp., Samsung Electronics Co. Ltd., Scality Inc., Toshiba Corp., and Western Digital Corp..

Key insights into market evolution with AI-powered analysis. Explore trends, segmentation, and growth drivers- View the snapshot of this report

Next-Generation Data Storage Market Scope

Report Coverage

Details

Base year

2023

Historic period

2018 – 2022

Forecast period

2024-2028

Growth momentum & CAGR

Accelerate at a CAGR of 8.08%

Market growth 2024-2028

USD 29.2 billion

Market structure

Fragmented

YoY growth 2022-2023 (%)

7.32

Regional analysis

North America, Europe, APAC, South America, and Middle East and Africa

Performing market contribution

Europe at 33%

Key countries

US, China, UK, France, and Japan

Key companies profiled

Cloudian Inc., DataDirect Networks Inc., Dell Technologies Inc., Drobo Inc., Furukawa Electric Co. Ltd., Hewlett Packard Enterprise Co., Hitachi Ltd., Inspur Group, International Business Machines Corp., Micron Technology Inc., NetApp Inc., Netgear Inc., Nutanix Inc., Oracle Corp., Pure Storage Inc., Quantum Corp., Samsung Electronics Co. Ltd., Scality Inc., Toshiba Corp., and Western Digital Corp.

 

Market Driver

Next-Generation Software Defined Storage (SDS) is a modern approach to enterprise data storage that separates software services, such as data administration, safety, and input/output capabilities, from hardware services. This separation enhances infrastructure flexibility, scalability, and automation capabilities. SDS also pools resources, abstracts hardware, and automates management, while supporting legacy applications, big data analytics, and cloud-based data apps. Vendors like EMC, NetApp, and IBM offer SDS-enabled infrastructure, making it a cost-effective alternative to reconfiguring existing arrays. Adopting new SSD arrays is more affordable than upgrading existing ones. SDS is increasingly essential due to the growing need for efficient data storage. 

The Next-Generation Data Storage Market is experiencing significant growth due to the exponential increase in digital data production from mobile devices, smart wearables, connected devices, and the Internet of Things. With the rollout of 5G technology, faster data transfer and lower latency are becoming essential for data-driven applications, analytics, and automated systems. The expansion of e-commerce, banking services, financial services, and online shopping is leading to massive amounts of less structured data. Security breaches, configuration errors, and poor user rights pose serious data security issues, making cloud storage and server services increasingly popular. Higher storage capacity, scalability, and flexibility are key requirements for large-scale industries handling corporate information, patient information, and financial data. The market is responding with high-speed data storage solutions, automatic cloud backups, and ransomware attack protection. The industry is poised for continued expansion as the world becomes more digitized. 

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 Market Challenges

Next-generation data storage market requires customized solutions based on end-user needs, resulting in costly research and development processes. Cloud service providers face demand fluctuations due to consumer trends, leading to potential oversupply or shortage situations. Complexity in designing next-generation storage solutions also poses a challenge to market growth. Vendors aim to align production with revenue, but unexpected changes in demand can disrupt manufacturing costs.The Next-Generation Data Storage Market is facing numerous challenges in today’s business landscape. Compliance with data protection regulations is a major concern for businesses, especially those in the BFSI, manufacturing, and consumer goods sectors. Data centers need to store vast amounts of data for cloud computing, big data, AI, machine learning, and social media, requiring efficient and secure storage solutions. Cyber threats such as malware, ransomware, viruses, worms, botnets, spam, spoofing, phishing, hacktivism, and state-sanctioned cyberwarfare pose significant risks to data integrity and privacy. Flash memory and HDDs from non-volatile manufacturers are crucial for addressing latency issues in mobile payments and tablets/laptops. On-premises storage systems must contend with FOBS systems and the need for high-performance, low-latency solutions. The market must adapt to these challenges to meet the evolving needs of businesses. PAC Storage (US) and other leading players are investing in advanced technologies to ensure secure, efficient, and cost-effective data storage solutions.

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Segment Overview

This next-generation data storage market report extensively covers market segmentation by

Application 1.1 SAN1.2 NAS1.3 DASDeployment 2.1 On-premise2.2 CloudGeography 3.1 North America3.2 Europe3.3 APAC3.4 South America3.5 Middle East and Africa

1.1 SAN- A Storage Area Network (SAN) is a dedicated high-speed network that connects next-generation storage devices to multiple servers. It moves data from the common user network and organizes it into an independent high-speed network, allowing each server to access storage devices. Enterprises are the primary adopters of SAN storage due to its better flexibility, availability, and performance compared to Direct Attached Storage (DAS) or Network Attached Storage (NAS). SAN is a local area network designed for handling large data volumes. It supports data storage, retrieval, and replication using high-end servers and multiple disk arrays. Vendors like Dell Technologies, Hewlett Packard Enterprise, and IBM offer SAN equipment, with costs ranging from hundreds to thousands of dollars. SAN solutions come in two types: Fibre Channel (FC) for mission-critical applications and iSCSI for IP networks. SAN offers advantages such as storage virtualization, high-speed disk technologies, centralized backup, and dynamic failover protection. The construction of data centers in developing countries is increasing, driving the adoption of SAN storage arrays. SAN solutions include Virtual SAN, Unified SAN, and Converged SAN, each offering unique benefits. Virtual SAN is implemented on a hypervisor, providing ease of management and scalability. Unified SAN exposes file and block storage through a single device. Converged SAN uses a common network infrastructure for different networks and keeps it separate from Ethernet networks.

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Research Analysis

The Next-Generation Data Storage market is experiencing exponential growth due to the growth in data production from mobile devices, smart wearables, and connected devices. With the rollout of 5G technology, faster data transfer and processing speeds are enabling new applications in e-commerce, mobile payments, and cloud computing. Smart technologies and automated systems are generating massive amounts of data, leading to an increased demand for efficient and secure data storage solutions. Security breaches and cyber threats are major concerns, driving the need for advanced encryption and data protection technologies. Cloud storage and data centers are becoming the go-to solutions for businesses and individuals seeking cost-effective and scalable storage solutions. Big data, analytics, AI, and machine learning are driving the need for high-performance storage solutions with low latency, such as Flash memory and non-volatile manufacturers. Social media, healthcare, and other data-intensive industries are also fueling the growth of the Next-Generation Data Storage market. HDDs continue to dominate the market due to their affordability and high storage capacity, but Flash memory is gaining popularity due to its faster read and write speeds. Distributed denial-of-service attacks and other cyber threats are also pushing the market towards more secure storage solutions. Overall, the Next-Generation Data Storage market is poised for significant growth in the coming years, driven by the increasing demand for efficient, secure, and scalable storage solutions for data generated by mobile devices, smart technologies, and other digital applications.

Market Research Overview

The next-generation data storage market is experiencing exponential growth due to the increasing production of digital data from mobile devices, smart wearables, connected devices, and the implementation of 5G technology. The expansion of e-commerce, smart technologies, and automated systems is also contributing to the industry’s growth. However, this growth brings new challenges such as security breaches, configuration errors, poor user rights, and data security issues. Large-scale industries, including healthcare, banking services, and financial services, generate vast amounts of less structured data that require scalable and flexible storage solutions. The healthcare sector, in particular, deals with sensitive patient information, making data protection and compliance essential. Cloud storage and server services are popular solutions for managing data, but they come with their own set of challenges, including data transfer, backup, and high-speed data storage. Ransomware attacks and other cyber threats pose significant risks, making data security a top priority. Direct-attached storage, network-attached storage, and storage area networks are on-premise solutions, while cloud, hybrid, and IT specialists offer installation and configuration services. The use of databases in retail, healthcare, and telecom companies, as well as in data centers, is increasing, making data security and compliance critical. The rise of mobile payments, cloud computing, big data, AI, machine learning, social media, and the Internet of Things is generating even more data, requiring new and innovative storage solutions to keep up with the demand. The market is expected to continue expanding as businesses and individuals seek to manage and protect their digital assets.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

ApplicationSANNASDASDeploymentOn-premiseCloudGeographyNorth AmericaEuropeAPACSouth AmericaMiddle East And Africa

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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SOURCE Technavio

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JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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Video: CNPC offers green chemical answer

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

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SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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