AI-Powered Storage Market Share
AI-powered storage is observed to gain traction on account of rise in data center establishments. The rise in demand for AI-powered storage in high performance compute (HPC) data centers is identified, which is expected to boost the expansion of the global AI-powered storage market. The surge in data generation and upscaling adoption of data analytics by sectors to aid in better and effective decision makings are drivers that can promote global AI-powered storage market. Additional growth impellers are better compliances and government guidelines with regards to generation of data. In addition, several enterprises are running on cloud-based services, such as virtual servers that can store data, which can be a boost for the expansion of the AI-powered storage market, worldwide.
Market Research Future (MRFR), studied dynamics of the global AI-powered storage market. In its revised “AI-Powered Storage Market” report, prepared by our experienced analysts, discusses forces that can alter the course of the market progress. MRFR study states that the global market of AI-powered storage is expected to surge at 17.56% CAGR from 2018 to 2025. In 2018, the AI-powered market was valued at USD 10.71 Bn. Rise in storage area network application of AI-powered storage is expected to cause the market size to increase. By 2025, the market is can touch USD 25.05 Bn.
The AI-powered storage market study was based on storage system, offerings, storage medium, storage architecture, and end use. The offerings-based segments of the market are software and hardware. The hardware segments are HDD, SSD, GPU, and CPU. The hardware segment can dominated in years to come. It is supposed to register a decent growth pace across the forecast span. The storage system-based segments are network-attached storage systems, direct-attached storage systems, and storage area network. The storage area network segment is lucrative and can win high profits for the market. The high utility of network-attached storage systems can prompt the AI-powered storage market growth.
Innovations in NAS systems can favor the market growth. For instance, in 2019, Synology, a Taiwan-based supplier of network-attached storage systems, observed its four new products gain international popularity, thereby prompting the expansion of the market. The storage architecture-based segments of the market are object storage, file storage, and block storage. The file storage segment can attain high valuation. The block storage segment appears a promising segment for the market expansion. The storage medium-based segments of the market are solid-state drive and hard disk drive.
The rise in sales figure of hard disk drive can prompt the global AI-powered storage market. AI enabled storage solutions can boost the expansion of the market. The cost-effectiveness of these storage devices can prompt the expansion of the market. The end use-based segments of the AI-powered storage market are healthcare, BFSI, retail, media & entertainment, telecommunication, manufacturing, and others. BFSI is a high-end user of AI-powered storage solutions, followed by information technology and telecommunication industries, due to the large volume of digital data they deal with. Telecos those adopting for AI enabled solutions to offer enhanced customer experience and effective network reliability are rising, thereby can boost the global powered storage market.
North America AI-powered storage market is likely to secure largest share of the market. The increased concentration of data storage marketers, easy obtainability of technical expertise, and penetration of AI in telecom, banking, and healthcare sectors can boost the regional market. Asia Pacific AI-powered technology market expansion can be shored-up by the adoption of effective cloud-based solutions. The adoption of robotics across manufacturing units can prompt the regional market growth. Flextronics International (Singapore), Tintri, Inc. (US), and Fujitsu (Japan) are some reputed companies in the AI-powered storage market.
More Information@ https://www.marketresearchfuture.com/reports/ai-powered-storage-market-8703
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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 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.
The solid-state drive is further bifurcated into all-flash array and hybrid flash array.
Hybrid flash array is witnessing high demand as they are cost-effective and provide high performance.Based on end use, the market has been segmented into BFSI, healthcare, media & entertainment, retail, manufacturing, telecommunication, and others.
The report "AI-Powered Storage Market by Offering (Hardware, Software), Storage System (DAS, NAS, SAN), Storage Architecture (File & Object-Based Storage), Storage Medium (SSD, HDD), & End User (Enterprises, CSP, Government, Telecom) - Global Forecast to 2024", is expected to grow from USD 10.4 billion in 2019 to USD 34.5 billion by 2024; growing at a CAGR of 27.1%.
Major factors driving the AI-powered storage market growth are the massive growth in data volumes, the need for global enterprise infrastructure to refresh their storage architecture, increasing adoption of cloud-based services, and growing demand for AI in HPC data centers.
Storage medium include solid-state drive (SSD) and hard disk drive (HDD).
File storage manages the layout, structure of files, and directories— cataloging structure, which contains references to other computer files on physical storage.
Within file- and object-based storage, object storage is gaining major market share as it helps handle huge unstructured data, unlike file storage, which is mainly used to store structured data.
It has also been the largest economy in the world, which has high disposable income leading to increased demand for modern technologies in the country, the investments in financial AI in the United States tripled from 2013 to 2014 to a total of USD 12.2 billion and also the AI deployment in the country gives them tremendous opportunities for pilot testing and future deployment.
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.
It is no longer enough to deploy capacity and connect faster drives or buy an all-flash array and assume that flash resolves all consumer problems.
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.
