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Global Virtual Machine Market to reach USD 101.77 billion by the end of 2030.

Global Virtual Machine Market Size study & Forecast, by Component (Hardware, Software, Combination Virtual Machine), by Type (Process Virtual Machine, System Virtual Machine), by Application (Large, SMEs) by Industry (Retail, Healthcare, Manufacturing, Government, Others) and Regional Analysis, 2023-2030

Product Code: ICTICTI-94155439
Publish Date: 19-06-2023
Page: 200

Global Virtual Machine Market is valued at approximately USD 23.2 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 20.3% over the forecast period 2023-2030. A computer system’s software implementation is known as a virtual machine. Users can do operations just as they would on a real computer to the way it creates a distinct copy of the latter. It is a piece of software that not only mimics the actions of another computer, but also carries out operations like starting up programs and applications on a different Machine. The virtual machine market Virtual Machine Market is increasing because of factors such as adoption of heavy applications among organizations and the rise in cloud computing technologies across the globe have fueled the demand for virtual machines. Moreover, virtual machines enable time and money saving for businesses. The global development of the IT sector is accelerating the market for virtual machines.

According to the International Energy Agency (IEA), The number of connected IoT devices is forecast to reach from 8.4 billion to 20 billion by 2020. Rising Digitalization Businesses and organizations are finding themselves in an increasingly complex network world. As businesses continue to generate a staggering volume of data daily, they are looking at transformation through automation and virtualization to optimize the cost and scale of experiences. There is an ongoing trend of using mobile devices, apps, and a variety of collaboration tools to communicate with other teams across geographies, platforms, and devices. Another major factor that drives the market is the rise in cloud computing technologies. Cloud computing helps in security measures to protect user’s data and ensure the privacy of sensitive information and also ,the changing IT consumption trends and increasing adoption of cloud computing solutions are creating potential growth opportunities for the virtual machine market In addition, the expansion of the virtual machine industry is being supported by the growing investments made in IT infrastructure transformation and digitalization by governments from different countries. However, lack of awareness of the virtual machine is restraining the growth of the Virtual Machine Market.

The key regions considered for the Global Virtual Machine Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the worldwide virtual machine market owing to the rising number of data centers and the region’s expanding IT sector. As per Statista, in 2022, the data center virtualization market recorded a revenue worth USD 7 billion. Furthermore, Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as rising government initiatives regarding virtual machines and rapid industrialization within the region.

Major market player included in this report are:

Amazon.com, Inc. (U.S.)
Citrix Systems Inc. (U.S.)
Hewlett Packard Enterprise Development LP (U.S.)
Huawei Technologies Co. Ltd. (U.S.)
Microsoft Corporation (U.S.)
Oracle Corporation (U.S.)
Parallels Inc. (U.S.)
Red Hat Inc. (U.S.)
Nutanix Inc. (U.S.)
Virtual Machine ware Inc. (U.S.)

Recent Developments in the market:
• In December 2020, the most recent version of VMware vSphere 7 was made available. The new update gives enterprises the tools they require for both conventional and cutting-edge applications and workloads, making it the most potent version of VMware vSphere to date.

• In June 2020, Microsoft made its Azure general-purpose and memory-optimized Virtual Machines based on the 2nd generation Intel Xeon Platinum 8272CL available, promising up to a 20% increase in CPU performance over the Dv3 and Ev3 VMs.

Global Virtual Machine Market Report Scope:
• Historical Data – 2020 – 2021
• Base Year for Estimation – 2022
• Forecast period – 2023-2030
• Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
• Segments Covered – Component, Type , Application, Industry, Region
• Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
• Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:
Hardware
Software
Combination

By Type:
Process virtual machine
System virtual machine

By Application:
Large
SMEs

By Industry:
Retail
Healthcare
Manufacturing
Government
Others

By Region:

North America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Virtual Machine Market, by Region, 2020-2030 (USD Billion)
1.2.2. Virtual Machine Market, by Component, 2020-2030 (USD Billion)
1.2.3. Virtual Machine Market, by Type, 2020-2030 (USD Billion)
1.2.4. Virtual Machine Market, by Application, 2020-2030 (USD Billion)
1.2.5. Virtual Machine Market, by Industry, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Virtual Machine Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Virtual Machine Market Dynamics
3.1. Virtual Machine Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increased usage of Virtual Machines across verticals
3.1.1.2. Rising Digitalisation and continuous growth of IT infrastructure
3.1.2. Market Challenges
3.1.2.1. Lack of awareness among end users
3.1.3. Market Opportunities
3.1.3.1. Advancements in Formulation
3.1.3.2. Development in IT infrastructure
Chapter 4. Global Virtual Machine Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Virtual Machine Market, by Component
5.1. Market Snapshot
5.2. Global Virtual Machine Market by Component, Performance – Potential Analysis
5.3. Global Virtual Machine Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Virtual Machine Market, Sub Segment Analysis
5.4.1. Hardware
5.4.2. Software
5.4.3. Combination
Chapter 6. Global Virtual Machine Market, by Type
6.1. Market Snapshot
6.2. Global Virtual Machine Market by Type, Performance – Potential Analysis
6.3. Global Virtual Machine Market Estimates & Forecasts by Type 2020-2030 (USD Billion)
6.4. Virtual Machine Market, Sub Segment Analysis
6.4.1. Process Virtual Machine
6.4.2. System Virtual Machine
Chapter 7. Global Virtual Machine Market, by Application
7.1. Market Snapshot
7.2. Global Virtual Machine Market by Application, Performance – Potential Analysis
7.3. Global Virtual Machine Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
7.4. Virtual Machine Market, Sub Segment Analysis
7.4.1. Large
7.4.2. SMEs
Chapter 8. Global Virtual Machine Market, by Industry
8.1. Market Snapshot
8.2. Global Virtual Machine Market by Industry, Performance – Potential Analysis
8.3. Global Virtual Machine Market Estimates & Forecasts by Industry 2020-2030 (USD Billion)
8.4. Virtual Machine Market, Sub Segment Analysis
8.4.1. Retail
8.4.2. Healthcare
8.4.3. Manufacturing
8.4.4. Government
8.4.5. Others
Chapter 9. Global Virtual Machine Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Virtual Machine Market, Regional Market Snapshot
9.4. North America Virtual Machine Market
9.4.1. U.S. Virtual Machine Market
9.4.1.1. Component breakdown estimates & forecasts, 2020-2030
9.4.1.2. Type breakdown estimates & forecasts, 2020-2030
9.4.1.3. application breakdown estimates & forecasts, 2020-2030
9.4.1.4. Industry breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Virtual Machine Market
9.5. Europe Virtual Machine Market Snapshot
9.5.1. U.K. Virtual Machine Market
9.5.2. Germany Virtual Machine Market
9.5.3. France Virtual Machine Market
9.5.4. Spain Virtual Machine Market
9.5.5. Italy Virtual Machine Market
9.5.6. Rest of Europe Virtual Machine Market
9.6. Asia-Pacific Virtual Machine Market Snapshot
9.6.1. China Virtual Machine Market
9.6.2. India Virtual Machine Market
9.6.3. Japan Virtual Machine Market
9.6.4. Australia Virtual Machine Market
9.6.5. South Korea Virtual Machine Market
9.6.6. Rest of Asia Pacific Virtual Machine Market
9.7. Latin America Virtual Machine Market Snapshot
9.7.1. Brazil Virtual Machine Market
9.7.2. Mexico Virtual Machine Market
9.8. Middle East & Africa Virtual Machine Market
9.8.1. Saudi Arabia Virtual Machine Market
9.8.2. South Africa Virtual Machine Market
9.8.3. Rest of Middle East & Africa Virtual Machine Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Amazon.com, Inc.(U.S)
10.3.1.1. Key Information
10.3.1.2. Overview
10.3.1.3. Financial (Subject to Data Availability)
10.3.1.4. Product Summary
10.3.1.5. Recent Developments
10.3.2. Citrix Systems Inc. (U.S.)
10.3.3. Hewlett Packard Enterprise Development LP (U.S.)
10.3.4. Huawei Technologies Co. Ltd. (U.S.)
10.3.5. Microsoft Corporation (U.S.)
10.3.6. Oracle Corporation (U.S.)
10.3.7. Parallels Inc. (U.S.)
10.3.8. Red Hat Inc. (U.S.)
10.3.9. Nutanix Inc. (U.S.)
10.3.10. Virtual Machine ware Inc. (U.S)

Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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