One of the key drivers of Al-powered storage market is the growth in adoption of cloud-based applications & services.
According to TechSci Research report, “AI Powered Storage Market - Industry Size, Share, Trends, Competition Forecast & Opportunities, 2029”. The Global AI Powered Storage is anticipated to project robust growth in the forecast period with a CAGR of 6.80% through 2029. One of the key drivers of Al-powered storage market is the growth in adoption of cloud-based applications & services. Cloud based applications have carried a massive revolution in the business industry, particularly during COVID-19 pandemic. Many companies are adopting cloud-based platforms as it bids limitless flexibility & reliability. Moreover, it proposals great adaptability & is eco-friendly which further pushes the AI powered storage market growth. The Al- powered storage is widely adopted due to the digitalization of the markets after the covid-19.
Companies are shifting all their workload to cloud based applications to ease distant working. Over the past few years, cloud migration has seen widespread global adoption, but recent trend to remote working has caused companies to rely more than ever on cloud services & apps. Massive volumes of data are required for artificial intelligence, which the cloud environment must process in real time and store for later use. This requires a high performance, adaptable, and flexible data storage system. The popularity of AI-powered storage is rising as demand for machine learning and artificial intelligence rises. Advanced analytics are used by AI-powered storage, which raises the demand for corporate infrastructure. Additionally, it is important for the uptake of connected devices and digitization.
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Artificial intelligence needs a large amount of data that could be processed in real-time and stored for future use in a cloud environment. Therefore, it requires a data storage solution for flexibility, scalable, and high performance.
AI and ML applications require data for functioning. The significant amount of data power training simulations and models that support decision-making and offer more effective and precise insights.
The AI-powered storage provides quick access from the data center to the cloud edge, as AI is based on cloud infrastructure. Storage, data collection, and applications could be spread across the cloud environment. AI storage enables quick access to data in the whole cloud, no matter whether it is stored or moved. The automation-led AI storage offers dynamic management of the file and resource permissions. It includes identity and access management configurations, as well as routing, load balancing plans, and processing directives. AI storage automates such functions for streamlining the operations of the system. The workloads may fluctuate over time, therefore, the workloads base on AI storage needs to cater to the demand without impacting them.
In such an application, the storage might get completely consumed. Better storage with excess capacity can alleviate the scaling and slowdown issues. AI applications offer cost-effective solutions through proper scalability and bulk storage management. It mitigates the need for purchasing, and resource maintenance, that is no longer needed. GPU-Accelerated Hardware: The quick data processing from storage to AI and machine learning algorithms require hardware for managing numerous parallel computing tasks. GPU acceleration-based cloud infrastructure enables such tasks for expanding storage, transmission, and processing of massive data required for supporting AI applications.
High-Performance Computing Clusters: HPC clusters include file systems, servers, and shared storage for quick scaling and supporting the heavy workloads associated with machine learning and artificial intelligence. A better configured HPC cluster that quickly provides local storage for the preparation of data for huge AI algorithms for building advanced artificial intelligence.
NVMe Flash Storage: Due to huge workloads, it is crucial to have quick storage retrieval. NVMe storage is located close to the GPU function as the real-time storage medium for AI applications that require quick access to data.
Solid-State Hard Drive: AI storage facilitates the longer-term storage located outside of NVMe flash. Moreover, systems require to shift away from spinning disk media to storage applications located outside of archives. The solid-state storage facilitates another layer of data access that reduces the access time and enhances efficiency.
Key market players in the Global AI Powered Storage Market are following:-
- Intel Corporation
- NVIDIA Corporation
- IBM
- Samsung Electronics
- Pure Storage
- NetApp
- Micron Technology
- CISCO
- Toshiba
- Hitachi
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“AI applications provide system analytics and business insights for huge cloud and IT infrastructure. Moreover, the AI storage optimizes HPC and hardware for developing more precise, responsive, insightful AI applications that reflects real-time data changes.. Moreover, the availability of real-time accurate data helps AI algorithms report and inform the administrators about the system problem. The presence of data and computing resources might help in precise reporting. The improved storage functions by utilizing automation for supporting key management features. Moreover, automation makes AI storage infrastructure more responsive to problems. It consists of documentation, responding to issues enabled by data transmissions, routing failovers in HPC clusters, and well as automated backups. AI-powered storage provides an agility level that can-not matches human-administered systems. It enhances the storage for intense workloads to provide it to machine learning. Such systems quickly respond to scaling demands, real-time issues, and system adjustments caused by technical issues.
Therefore, AI-powered storage is widely adopted for catering to the workload demands, with quick access to massive amounts of data in real-time, without hindering workloads. said Mr. Karan Chechi, Research Director with TechSci Research, a research-based global management consulting firm.
AI Powered Storage Market – Global Industry Size, Share, Trends, Opportunity, and Forecast Segmented By Offerings (Hardware, Software, Storage System, Storage Architecture, and Storage Medium), By End-User (BFSI, Healthcare, Media & Entertainment, Retail, Manufacturing, Telecommunication), By Region, Competition 2019-2029. has evaluated the future growth potential of Global AI Powered Storage Market and provides statistics and information on market structure, size, share, and future growth. The report is intended to provide cutting-edge market intelligence and help decision makers take sound investment decisions. Besides, the report also identifies and analyzes the emerging trends along with essential drivers, challenges, and opportunities present in the Global AI Powered Storage Market.
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AI and machine learning workloads require vast amounts of storage to extract translate and load input data, do exploratory data analysis to see what data is relevant, create test data, build and train the models, retrain the models to reflect changing data patterns, inferences, and discoveries and keep them running.
Data does not lose value, so data must be retained for as long as there is perceived value, and regulatory requirements like GDPR may require retention of data in a form that explains the decisions made by AI.
Scalability includes the ability to minimize the footprint and cost of storage through intelligent use of deduplication, compression, virtualization, tiering, archiving, indexing cataloging, and shredding.The efficacies of AI infrastructure generally focus on computing hardware like the general-purpose CPUs, GPUs, FPGAs, and tensor processing units.
It is astute to keep a potent compute engine well-utilized, which needs feeding it with vast amounts of information as fast as possible.
There are numerous phases with different processing requirements, from model deployment, data ingestion, data discovery and visualization, data engineering, model development and training, and retention, all with various performance, tiering, and protocol requirements.
Factors such as the growing implementation of cloud-based services, a rise in the number of hyperscale data centers, and the deployment of data analytics tools across small and medium enterprises have positively impacted the demand for AI-powered storage.
AI-Powered Storage Market Trends A new market study, titled “AI-Powered Storage Market Trends ” has been featured on Market Research Future.According to Market Research Future, the market for the global AI-powered storage has been segmented on the basis of type, application, industry, and region.The rise adoption of technologies such as machine learning, artificial intelligence, and data analytics has led to an increase in data that require high storage capacity.
The enterprises are registering a need for a refreshed AI-based storage architecture.
Factors such as the growing adoption of cloud-based services, a rise in the number of hyperscale data centers, and the deployment of data analytics tools across small and medium enterprises have positively impacted the demand for AI-powered storage.
However, the network-attached storage systems segment is expected to register the highest CAGR during the forecast period from 2019 to 2025 owing to the multiple client access feature that it provides.Based on storage architecture, the market has been segmented into file storage, object storage, and block storage.
In 2018, western digital launched a new range of hard drive—Purple—for upcoming Digital Video Recorder and Network Video Recorder systems that feature Artificial Intelligence (AI) capabilities.
The solid-state drive is further bifurcated into all-flash array and hybrid flash array.
