The global market for Hyperscale Data Centers was estimated at US$170.0 Billion in 2023 and is projected to reach US$730.2 Billion by 2030, growing at a CAGR of 23.1% from 2023 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions.
The significance of hyperscale data centers lies in their ability to handle the exponential growth of data, provide the foundation for cloud computing, and support the operations of large enterprises and web-scale applications. Hyperscale facilities are engineered for energy efficiency, resiliency, and massive scalability, which allows cloud providers to offer on-demand computing resources to businesses around the world. These data centers enable the seamless delivery of a wide array of digital services, from social media and streaming platforms to artificial intelligence (AI) and machine learning (ML) applications. As the digital economy continues to expand, hyperscale data centers are essential for supporting the infrastructure that powers modern technology and drives innovation.
Energy efficiency has also seen significant improvements in hyperscale data centers, largely due to advances in cooling technologies and power management. Traditional data centers often consume vast amounts of energy to keep servers and other equipment cool, but hyperscale facilities are now incorporating innovative cooling methods such as liquid cooling, immersion cooling, and free-air cooling to reduce energy consumption. Liquid cooling, for example, transfers heat directly from servers to a liquid coolant, making it more efficient than traditional air-cooling systems. This not only lowers operating costs but also reduces the carbon footprint of hyperscale data centers, making them more sustainable. The use of renewable energy sources such as solar and wind power is another critical advancement in energy management, with major operators committing to powering their data centers with clean energy.
Hyperscale data centers have also benefitted from advances in server hardware, particularly with the adoption of high-performance, low-power processors such as ARM-based chips and specialized hardware for artificial intelligence (AI) and machine learning (ML). These processors are designed to handle the heavy workloads of AI, big data analytics, and cloud computing while consuming less power than traditional CPUs. The integration of graphics processing units (GPUs) and tensor processing units (TPUs) into hyperscale data centers has further boosted their ability to process complex AI tasks, enabling faster computations and more efficient handling of large datasets. These advancements in hardware have made hyperscale data centers more efficient in terms of both performance and energy use.
The advent of software-defined infrastructure (SDI) is another major technological advancement that has transformed hyperscale data centers. In an SDI environment, software abstracts hardware resources - such as compute, storage, and networking - allowing data center operators to manage and optimize these resources more efficiently. Software-defined networking (SDN) and software-defined storage (SDS) enable data center operators to allocate resources dynamically based on workload demands, improving flexibility and scalability. SDI also allows for greater automation, reducing the need for manual intervention in tasks like provisioning, scaling, and load balancing. By leveraging SDI, hyperscale data centers can operate more efficiently, reduce costs, and offer on-demand services to customers at scale.
Advances in edge computing have further extended the capabilities of hyperscale data centers by decentralizing data processing and bringing computation closer to end-users. Edge computing reduces latency and improves performance by processing data locally at the edge of the network, rather than relying solely on centralized hyperscale data centers. This is particularly important for applications that require real-time processing, such as autonomous vehicles, the Internet of Things (IoT), and augmented reality (AR) platforms. Hyperscale data centers are increasingly being integrated with edge computing nodes, creating a more distributed infrastructure that balances the need for both centralized and decentralized computing power.
Storage technologies have also seen advancements that improve the efficiency and scalability of hyperscale data centers. Solid-state drives (SSDs) and NVMe (Non-Volatile Memory Express) storage have become standard in hyperscale environments due to their speed, durability, and lower power consumption compared to traditional hard disk drives (HDDs). These storage solutions enable faster data access and improved performance for applications that require high-speed data retrieval, such as AI and real-time analytics. Additionally, advancements in data deduplication, compression, and tiered storage architectures have optimized the use of storage resources, further enhancing the efficiency of hyperscale data centers.
The use of artificial intelligence (AI) and machine learning (ML) to manage and optimize data center operations is another significant technological advancement in hyperscale data centers. AI-driven tools can analyze vast amounts of data generated by the data center's operations, identifying patterns and making real-time adjustments to optimize resource allocation, energy usage, and cooling systems. For example, AI can predict when a server might fail and reroute workloads to prevent downtime, or it can adjust cooling systems based on real-time temperature data to improve energy efficiency. The integration of AI into hyperscale data center management allows operators to optimize performance, reduce operational costs, and improve sustainability.
Big data analytics is another area where hyperscale data centers play a crucial role. The volume of data generated by businesses, consumers, and IoT devices is growing exponentially, and processing and analyzing this data require massive computational resources. Hyperscale data centers provide the storage capacity and processing power necessary to handle big data workloads, enabling organizations to derive valuable insights from their data. Whether it's analyzing customer behavior, optimizing supply chains, or powering AI-driven applications, hyperscale data centers are essential for processing the vast datasets that drive business intelligence and decision-making in today's data-driven world.
Hyperscale data centers also serve as the foundation for many of the digital services that businesses and consumers rely on daily. From video streaming platforms like Netflix to social media networks like Facebook, hyperscale facilities ensure that these services can scale to accommodate millions of users simultaneously without experiencing performance issues. These data centers are engineered for high availability, redundancy, and fault tolerance, ensuring that digital services remain online and accessible 24/7. In an increasingly digital world, where everything from entertainment to e-commerce depends on cloud-based platforms, hyperscale data centers provide the reliable infrastructure needed to keep these services running smoothly.
In addition to cloud computing and big data, hyperscale data centers are critical for enabling digital transformation across industries. Digital transformation involves leveraging technology to improve business processes, customer experiences, and operational efficiency. Hyperscale data centers allow businesses to adopt technologies such as AI, machine learning, and automation to optimize their operations and deliver innovative services. For example, retail companies can use cloud-based AI platforms to analyze customer data and deliver personalized shopping experiences, while manufacturers can implement IoT solutions to monitor equipment and optimize production processes. Hyperscale data centers provide the scalable infrastructure required to support these transformative technologies.
Another reason hyperscale data centers are so important is their role in supporting global connectivity. These data centers host critical infrastructure for telecommunications networks, cloud services, and content delivery networks (CDNs) that enable businesses to operate across borders and serve customers worldwide. Hyperscale data centers are often located in strategic locations around the globe, allowing businesses to deploy applications and services closer to their users, reducing latency and improving performance. This global reach is essential for companies that need to deliver high-quality digital experiences to customers in multiple regions.
Furthermore, hyperscale data centers provide the necessary infrastructure for AI and machine learning workloads, which are becoming increasingly important in fields such as healthcare, finance, and autonomous systems. AI and ML models require enormous amounts of data and computational power to train and deploy, and hyperscale data centers offer the processing capabilities needed to handle these complex workloads. By leveraging the scalability and power of hyperscale infrastructure, businesses can develop and deploy AI-driven applications that drive innovation and efficiency across industries.
Hyperscale data centers are also critical for supporting the growing demand for edge computing. As more devices become connected to the internet and generate data at the edge of the network, businesses need infrastructure that can process data in real time, close to where it is generated. Hyperscale data centers are increasingly being integrated with edge computing nodes, providing the necessary backbone for edge-to-cloud architectures. This integration allows businesses to process data at the edge while leveraging the compute and storage capabilities of centralized hyperscale facilities for long-term storage and analytics.
The rise of big data analytics is another significant factor contributing to the growth of the hyperscale data center market. Organizations across industries are collecting and analyzing massive amounts of data to gain insights and make data-driven decisions. Processing these large datasets requires substantial computing power and storage capacity, which hyperscale data centers provide. As the amount of data generated by IoT devices, social media, and digital transactions continues to grow, the demand for hyperscale data centers capable of handling big data workloads will only increase.
The increasing use of artificial intelligence and machine learning is also fueling the growth of the hyperscale data center market. AI and ML applications require powerful hardware, such as GPUs and specialized processors, to train complex models and process large datasets. Hyperscale data centers are equipped with the necessary infrastructure to support AI workloads, making them essential for companies developing AI-driven applications in fields such as healthcare, finance, and autonomous systems. As AI adoption grows, hyperscale data centers will play a critical role in providing the computational power needed for these advanced technologies.
Energy efficiency and sustainability are becoming more important factors in the growth of hyperscale data centers. With data centers consuming vast amounts of electricity, there is increasing pressure on operators to reduce their environmental impact. Hyperscale data centers are designed with energy efficiency in mind, incorporating advanced cooling technologies, renewable energy sources, and power management systems to reduce energy consumption. Major cloud providers are committing to sustainability goals, such as powering their data centers with 100% renewable energy and achieving carbon neutrality. The focus on sustainability is driving investments in hyperscale data centers that are designed to operate efficiently while minimizing their environmental footprint.
The rise of 5G and the Internet of Things (IoT) is also contributing to the expansion of the hyperscale data center market. 5G networks enable faster data transmission and support a growing number of connected devices, generating vast amounts of data that need to be processed in real-time. Hyperscale data centers, with their ability to scale quickly and handle large data volumes, are essential for supporting the growth of 5G and IoT applications. As industries such as automotive, manufacturing, and healthcare adopt IoT solutions, the demand for hyperscale infrastructure to process and store data will continue to grow.
Another factor driving the growth of hyperscale data centers is the increasing need for edge computing. As businesses deploy edge computing nodes to process data closer to the source, hyperscale data centers serve as the central hubs for storing, analyzing, and managing the data generated at the edge. The integration of hyperscale and edge computing infrastructures allows organizations to achieve a balance between real-time data processing and long-term data storage, supporting applications that require both low latency and high computational power.
Investments by major cloud providers and tech companies are also accelerating the growth of the hyperscale data center market. Companies like Amazon, Microsoft, Google, and Facebook continue to invest heavily in building new hyperscale data centers around the world to meet the growing demand for cloud services and digital applications. These investments are driving the construction of state-of-the-art data centers that are designed to handle massive workloads efficiently, scale seamlessly, and operate sustainably.
With the increasing demand for cloud services, big data analytics, AI, and edge computing, the hyperscale data center market is poised for continued growth. As businesses rely more on digital platforms and scalable infrastructure, hyperscale data centers will remain at the core of the global IT landscape, powering the future of cloud computing, AI, and the digital economy.
Are Hyperscale Data Centers the Backbone of Cloud Computing and the Digital Economy?
Hyperscale data centers are becoming the backbone of global IT infrastructure, but why are they so crucial for cloud computing, big data, and the digital economy? Hyperscale data centers are massive facilities designed to support large-scale cloud services, big data analytics, and large enterprises that require significant computing power, storage, and networking capabilities. These data centers are typically operated by major cloud providers such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and Facebook, among others. A hyperscale data center is defined by its ability to scale efficiently as demand grows, enabling organizations to add thousands of servers and other hardware components seamlessly without compromising performance or efficiency.The significance of hyperscale data centers lies in their ability to handle the exponential growth of data, provide the foundation for cloud computing, and support the operations of large enterprises and web-scale applications. Hyperscale facilities are engineered for energy efficiency, resiliency, and massive scalability, which allows cloud providers to offer on-demand computing resources to businesses around the world. These data centers enable the seamless delivery of a wide array of digital services, from social media and streaming platforms to artificial intelligence (AI) and machine learning (ML) applications. As the digital economy continues to expand, hyperscale data centers are essential for supporting the infrastructure that powers modern technology and drives innovation.
How Have Technological Advancements Enhanced Hyperscale Data Centers for Greater Efficiency and Scalability?
Technological advancements have significantly enhanced the efficiency, scalability, and performance of hyperscale data centers, allowing them to meet the growing demands of cloud services, artificial intelligence, and global connectivity. One of the most critical advancements has been the development of modular data center designs. Modular data centers allow hyperscale operators to add capacity in a standardized and efficient manner. Instead of constructing entire facilities at once, operators can deploy pre-fabricated modules - such as power and cooling units, server racks, and networking components - that can be scaled up or down as needed. This modular approach allows hyperscale data centers to grow incrementally based on demand, minimizing upfront capital costs and enabling faster deployment.Energy efficiency has also seen significant improvements in hyperscale data centers, largely due to advances in cooling technologies and power management. Traditional data centers often consume vast amounts of energy to keep servers and other equipment cool, but hyperscale facilities are now incorporating innovative cooling methods such as liquid cooling, immersion cooling, and free-air cooling to reduce energy consumption. Liquid cooling, for example, transfers heat directly from servers to a liquid coolant, making it more efficient than traditional air-cooling systems. This not only lowers operating costs but also reduces the carbon footprint of hyperscale data centers, making them more sustainable. The use of renewable energy sources such as solar and wind power is another critical advancement in energy management, with major operators committing to powering their data centers with clean energy.
Hyperscale data centers have also benefitted from advances in server hardware, particularly with the adoption of high-performance, low-power processors such as ARM-based chips and specialized hardware for artificial intelligence (AI) and machine learning (ML). These processors are designed to handle the heavy workloads of AI, big data analytics, and cloud computing while consuming less power than traditional CPUs. The integration of graphics processing units (GPUs) and tensor processing units (TPUs) into hyperscale data centers has further boosted their ability to process complex AI tasks, enabling faster computations and more efficient handling of large datasets. These advancements in hardware have made hyperscale data centers more efficient in terms of both performance and energy use.
The advent of software-defined infrastructure (SDI) is another major technological advancement that has transformed hyperscale data centers. In an SDI environment, software abstracts hardware resources - such as compute, storage, and networking - allowing data center operators to manage and optimize these resources more efficiently. Software-defined networking (SDN) and software-defined storage (SDS) enable data center operators to allocate resources dynamically based on workload demands, improving flexibility and scalability. SDI also allows for greater automation, reducing the need for manual intervention in tasks like provisioning, scaling, and load balancing. By leveraging SDI, hyperscale data centers can operate more efficiently, reduce costs, and offer on-demand services to customers at scale.
Advances in edge computing have further extended the capabilities of hyperscale data centers by decentralizing data processing and bringing computation closer to end-users. Edge computing reduces latency and improves performance by processing data locally at the edge of the network, rather than relying solely on centralized hyperscale data centers. This is particularly important for applications that require real-time processing, such as autonomous vehicles, the Internet of Things (IoT), and augmented reality (AR) platforms. Hyperscale data centers are increasingly being integrated with edge computing nodes, creating a more distributed infrastructure that balances the need for both centralized and decentralized computing power.
Storage technologies have also seen advancements that improve the efficiency and scalability of hyperscale data centers. Solid-state drives (SSDs) and NVMe (Non-Volatile Memory Express) storage have become standard in hyperscale environments due to their speed, durability, and lower power consumption compared to traditional hard disk drives (HDDs). These storage solutions enable faster data access and improved performance for applications that require high-speed data retrieval, such as AI and real-time analytics. Additionally, advancements in data deduplication, compression, and tiered storage architectures have optimized the use of storage resources, further enhancing the efficiency of hyperscale data centers.
The use of artificial intelligence (AI) and machine learning (ML) to manage and optimize data center operations is another significant technological advancement in hyperscale data centers. AI-driven tools can analyze vast amounts of data generated by the data center's operations, identifying patterns and making real-time adjustments to optimize resource allocation, energy usage, and cooling systems. For example, AI can predict when a server might fail and reroute workloads to prevent downtime, or it can adjust cooling systems based on real-time temperature data to improve energy efficiency. The integration of AI into hyperscale data center management allows operators to optimize performance, reduce operational costs, and improve sustainability.
Why Are Hyperscale Data Centers Critical for Cloud Computing, Big Data, and Digital Transformation?
Hyperscale data centers are critical for cloud computing, big data, and digital transformation because they provide the massive computing power, storage capacity, and networking resources required to support the rapid growth of digital services and applications. One of the key reasons hyperscale data centers are so important is their ability to deliver on-demand computing resources through the cloud. Cloud service providers like AWS, Microsoft Azure, and Google Cloud rely on hyperscale data centers to offer scalable and flexible cloud computing platforms that can handle everything from small business applications to large-scale enterprise workloads. These platforms enable businesses to access vast amounts of computing power without having to invest in their own infrastructure, reducing costs and increasing agility.Big data analytics is another area where hyperscale data centers play a crucial role. The volume of data generated by businesses, consumers, and IoT devices is growing exponentially, and processing and analyzing this data require massive computational resources. Hyperscale data centers provide the storage capacity and processing power necessary to handle big data workloads, enabling organizations to derive valuable insights from their data. Whether it's analyzing customer behavior, optimizing supply chains, or powering AI-driven applications, hyperscale data centers are essential for processing the vast datasets that drive business intelligence and decision-making in today's data-driven world.
Hyperscale data centers also serve as the foundation for many of the digital services that businesses and consumers rely on daily. From video streaming platforms like Netflix to social media networks like Facebook, hyperscale facilities ensure that these services can scale to accommodate millions of users simultaneously without experiencing performance issues. These data centers are engineered for high availability, redundancy, and fault tolerance, ensuring that digital services remain online and accessible 24/7. In an increasingly digital world, where everything from entertainment to e-commerce depends on cloud-based platforms, hyperscale data centers provide the reliable infrastructure needed to keep these services running smoothly.
In addition to cloud computing and big data, hyperscale data centers are critical for enabling digital transformation across industries. Digital transformation involves leveraging technology to improve business processes, customer experiences, and operational efficiency. Hyperscale data centers allow businesses to adopt technologies such as AI, machine learning, and automation to optimize their operations and deliver innovative services. For example, retail companies can use cloud-based AI platforms to analyze customer data and deliver personalized shopping experiences, while manufacturers can implement IoT solutions to monitor equipment and optimize production processes. Hyperscale data centers provide the scalable infrastructure required to support these transformative technologies.
Another reason hyperscale data centers are so important is their role in supporting global connectivity. These data centers host critical infrastructure for telecommunications networks, cloud services, and content delivery networks (CDNs) that enable businesses to operate across borders and serve customers worldwide. Hyperscale data centers are often located in strategic locations around the globe, allowing businesses to deploy applications and services closer to their users, reducing latency and improving performance. This global reach is essential for companies that need to deliver high-quality digital experiences to customers in multiple regions.
Furthermore, hyperscale data centers provide the necessary infrastructure for AI and machine learning workloads, which are becoming increasingly important in fields such as healthcare, finance, and autonomous systems. AI and ML models require enormous amounts of data and computational power to train and deploy, and hyperscale data centers offer the processing capabilities needed to handle these complex workloads. By leveraging the scalability and power of hyperscale infrastructure, businesses can develop and deploy AI-driven applications that drive innovation and efficiency across industries.
Hyperscale data centers are also critical for supporting the growing demand for edge computing. As more devices become connected to the internet and generate data at the edge of the network, businesses need infrastructure that can process data in real time, close to where it is generated. Hyperscale data centers are increasingly being integrated with edge computing nodes, providing the necessary backbone for edge-to-cloud architectures. This integration allows businesses to process data at the edge while leveraging the compute and storage capabilities of centralized hyperscale facilities for long-term storage and analytics.
What Factors Are Driving the Growth of the Hyperscale Data Center Market?
Several factors are driving the rapid growth of the hyperscale data center market, including the increasing adoption of cloud services, the rise of big data and artificial intelligence, and the demand for scalable, energy-efficient infrastructure. One of the primary drivers is the growing adoption of cloud computing by businesses of all sizes. As more companies migrate their workloads to the cloud to reduce costs, improve scalability, and enhance flexibility, the demand for hyperscale data centers has surged. Cloud providers such as AWS, Microsoft Azure, and Google Cloud are expanding their global data center footprints to meet the growing demand for cloud services, driving the need for more hyperscale facilities.The rise of big data analytics is another significant factor contributing to the growth of the hyperscale data center market. Organizations across industries are collecting and analyzing massive amounts of data to gain insights and make data-driven decisions. Processing these large datasets requires substantial computing power and storage capacity, which hyperscale data centers provide. As the amount of data generated by IoT devices, social media, and digital transactions continues to grow, the demand for hyperscale data centers capable of handling big data workloads will only increase.
The increasing use of artificial intelligence and machine learning is also fueling the growth of the hyperscale data center market. AI and ML applications require powerful hardware, such as GPUs and specialized processors, to train complex models and process large datasets. Hyperscale data centers are equipped with the necessary infrastructure to support AI workloads, making them essential for companies developing AI-driven applications in fields such as healthcare, finance, and autonomous systems. As AI adoption grows, hyperscale data centers will play a critical role in providing the computational power needed for these advanced technologies.
Energy efficiency and sustainability are becoming more important factors in the growth of hyperscale data centers. With data centers consuming vast amounts of electricity, there is increasing pressure on operators to reduce their environmental impact. Hyperscale data centers are designed with energy efficiency in mind, incorporating advanced cooling technologies, renewable energy sources, and power management systems to reduce energy consumption. Major cloud providers are committing to sustainability goals, such as powering their data centers with 100% renewable energy and achieving carbon neutrality. The focus on sustainability is driving investments in hyperscale data centers that are designed to operate efficiently while minimizing their environmental footprint.
The rise of 5G and the Internet of Things (IoT) is also contributing to the expansion of the hyperscale data center market. 5G networks enable faster data transmission and support a growing number of connected devices, generating vast amounts of data that need to be processed in real-time. Hyperscale data centers, with their ability to scale quickly and handle large data volumes, are essential for supporting the growth of 5G and IoT applications. As industries such as automotive, manufacturing, and healthcare adopt IoT solutions, the demand for hyperscale infrastructure to process and store data will continue to grow.
Another factor driving the growth of hyperscale data centers is the increasing need for edge computing. As businesses deploy edge computing nodes to process data closer to the source, hyperscale data centers serve as the central hubs for storing, analyzing, and managing the data generated at the edge. The integration of hyperscale and edge computing infrastructures allows organizations to achieve a balance between real-time data processing and long-term data storage, supporting applications that require both low latency and high computational power.
Investments by major cloud providers and tech companies are also accelerating the growth of the hyperscale data center market. Companies like Amazon, Microsoft, Google, and Facebook continue to invest heavily in building new hyperscale data centers around the world to meet the growing demand for cloud services and digital applications. These investments are driving the construction of state-of-the-art data centers that are designed to handle massive workloads efficiently, scale seamlessly, and operate sustainably.
With the increasing demand for cloud services, big data analytics, AI, and edge computing, the hyperscale data center market is poised for continued growth. As businesses rely more on digital platforms and scalable infrastructure, hyperscale data centers will remain at the core of the global IT landscape, powering the future of cloud computing, AI, and the digital economy.
Key Insights:
- Market Growth: Understand the significant growth trajectory of the Cloud Providers Application segment, which is expected to reach US$358.6 Billion by 2030 with a CAGR of a 24.0%. The Colocation Providers Application segment is also set to grow at 23.2% CAGR over the analysis period.
- Regional Analysis: Gain insights into the U.S. market, which was valued at $48.8 Billion in 2023, and China, forecasted to grow at an impressive 22.4% CAGR to reach $111.2 Billion by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.
Why You Should Buy This Report:
- Detailed Market Analysis: Access a thorough analysis of the Global Hyperscale Data Centers Market, covering all major geographic regions and market segments.
- Competitive Insights: Get an overview of the competitive landscape, including the market presence of major players across different geographies.
- Future Trends and Drivers: Understand the key trends and drivers shaping the future of the Global Hyperscale Data Centers Market.
- Actionable Insights: Benefit from actionable insights that can help you identify new revenue opportunities and make strategic business decisions.
Key Questions Answered:
- How is the Global Hyperscale Data Centers Market expected to evolve by 2030?
- What are the main drivers and restraints affecting the market?
- Which market segments will grow the most over the forecast period?
- How will market shares for different regions and segments change by 2030?
- Who are the leading players in the market, and what are their prospects?
Report Features:
- Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2023 to 2030.
- In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
- Company Profiles: Coverage of major players such as Broadcom Ltd., Cavium, Inc., Cisco Systems, Inc., and more.
- Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.
Select Competitors (Total 22 Featured):
- Broadcom Ltd.
- Cavium, Inc.
- Cisco Systems, Inc.
- Dell Technologies
- Ericsson AB
- HPE (Hewlett Packard Enterprise India Pvt. Ltd.)
- Huawei Enterprise
- IBM Corporation
- Intel Corporation
- Lenovo Group Limited
- NVIDIA Corporation
- Quanta Computer, Inc.
Table of Contents
I. METHODOLOGYII. EXECUTIVE SUMMARY2. FOCUS ON SELECT PLAYERSIII. MARKET ANALYSISIV. COMPETITION
1. MARKET OVERVIEW
3. MARKET TRENDS & DRIVERS
4. GLOBAL MARKET PERSPECTIVE
UNITED STATES
CANADA
JAPAN
CHINA
EUROPE
FRANCE
GERMANY
ITALY
UNITED KINGDOM
REST OF EUROPE
ASIA-PACIFIC
REST OF WORLD
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Broadcom Ltd.
- Cavium, Inc.
- Cisco Systems, Inc.
- Dell Technologies
- Ericsson AB
- HPE (Hewlett Packard Enterprise India Pvt. Ltd.)
- Huawei Enterprise
- IBM Corporation
- Intel Corporation
- Lenovo Group Limited
- NVIDIA Corporation
- Quanta Computer, Inc.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 184 |
| Published | November 2024 |
| Forecast Period | 2023 - 2030 |
| Estimated Market Value ( USD | $ 170 Billion |
| Forecasted Market Value ( USD | $ 730.2 Billion |
| Compound Annual Growth Rate | 23.1% |
| Regions Covered | Global |
