HPC Data Management Market, 2024 report by The Business Research Company offers comprehensive insights into the current state of the market and highlights future growth opportunities.
Market Size –
The HPC data management market size has grown rapidly in recent years. It will grow from $30.98 billion in 2023 to $36.81 billion in 2024 at a compound annual growth rate (CAGR) of 18.8%. The growth in the historic period can be attributed to increasing demand for data storage and management, rising investments, increasing data complexity, rise of artificial intelligence (AI), and expansion of scientific research.
The HPC data management market size is expected to see rapid growth in the next few years. It will grow to $68.38 billion in 2028 at a compound annual growth rate (CAGR) of 16.7%. The growth in the forecast period can be attributed to exponential growth in data volume, convergence of HPC and ai, edge computing expansion, rapid technological innovations. Major trends in the forecast period include edge-to-cloud integration, quantum computing impact, enhanced security measures, AI-driven data management, collaborative research initiatives, exascale computing adoption.
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Scope Of HPC Data Management Market
The Business Research Company’s reports encompass a wide range of information, including:
- Market Size (Historic and Forecast): Analysis of the market’s historical performance and projections for future growth.
- Drivers: Examination of the key factors propelling market growth.
- Trends: Identification of emerging trends and patterns shaping the market landscape.
- Key Segments: Breakdown of the market into its primary segments and their respective performance.
- Focus Regions and Geographies: Insight into the most critical regions and geographical areas influencing the market.
- Macro Economic Factors: Assessment of broader economic elements impacting the market.
HPC Data Management Market Overview
Market Drivers –
The increasing data volumes are expected to propel the growth of the HPC data management market going forward. Data volumes refer to the quantity or amount of information generated, collected, or stored within a specific system or over a given period. HPC systems are crucial in performing intricate scientific simulations and research across various fields, such as climate modeling, genomics, drug discovery, and astrophysics. These scientific pursuits produce extensive datasets necessitating advanced data management solutions for efficient storage, retrieval, and analysis. As research initiatives increasingly rely on data and computational resources, a rising need for HPC data management solutions is needed to cater to these requirements. For instance, in December 2022, according to data from Augusta Free Press, a US-based news service company, global digital transformation spending was about $1.85 trillion, 16% more than in 2021, indicating data volumes are increasing. Therefore, increasing data volumes are expected to propel the growth of the HPC data management market going forward.
Market Trends –
Major companies operating in the HPC data management market are focusing on developing innovative solutions, such as the ActiveStor ultra-edge platform, to meet the growing demand. ActiveStor ultra-edge is a high-performance computing (HPC) and artificial intelligence or machine learning (AI/ML) storage solution for edge computing. It is a portable file system that can work on any adequately configured hardware and supports industry-standard NFS and SMB client protocols. For instance, in May 2023, Panasas Inc., a US-based data storage company, launched the ActiveStor ultra-edge platform, an HPC and AI/ML solution designed for edge computing environments. It reduces footprint and lowers entry costs, making it an ideal choice for organizations deploying HPC and AI/ML applications at remote locations closer to where data is generated to improve real-time decision-making. High-performance computing (HPC) data management is pivotal in facilitating the seamless integration of artificial intelligence (AI) by providing the necessary infrastructure for processing and analyzing vast datasets at accelerated speeds. The efficient storage, retrieval, and manipulation of data within an HPC environment are crucial for supporting AI algorithms that heavily rely on large-scale datasets for training and inference.
The HPC data management market covered in this report is segmented –
1) By Type: High Performance Computing (HPC), Data Analysis, Storage And Management, Other Types
2) By Services: Data Analysis Software, Data Analysis Workbenches
3) By Application: Life Sciences Research, Drug Discovery And Development, Clinical Trials, Other Applications
4) By End-User: Academic And Research Institutes, Pharmaceutical And Biotechnology Companies, Hospitals And Diagnostic Centers, Other End-Users
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Regional Insights –
North America was the largest region in the HPC data management market in 2023. The regions covered in the hpc data management market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
Key Companies –
Major companies operating in the HPC data management market are Dell Inc., Lenovo Group Limited, Intel Corporation, IBM Corporation, Cisco Systems Inc., Fujitsu Limited, Micron Technology Inc., Hewlett Packard Enterprise Company, NVIDIA Corporation, Advanced Micro Devices Inc., Huawei Technologies Co. Ltd., Seagate Technology Holdings plc, NetApp Inc., Super Micro Computer Inc., Illumina Inc., Arista Networks Inc., Pure Storage Inc., Inspur Group Co. Ltd., Quantum Corporation, DataDirect Networks Inc., Cohesity Inc., WekaIO Inc., Qumulo Inc., Scality Inc., Panasas Inc., Cary Inc., Excelero Inc., Infinidat Ltd
Table of Contents
- Executive Summary
- HPC Data Management Market Report Structure
- HPC Data Management Market Trends And Strategies
- HPC Data Management Market – Macro Economic Scenario
- HPC Data Management Market Size And Growth
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- HPC Data Management Market Competitor Landscape And Company Profiles
- Key Mergers And Acquisitions
- Future Outlook and Potential Analysis
- Appendix
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