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GPU database processes huge data volumes quicker and more effectively than CPUs because they operate in parallel instead of in sequence. GPUs speed up location-based and in-memory analysis, machine learning, and AI. With thousands of computing cores readily accessible on a single card, it is possible to execute functions in parallel, using brute force to solve complex analytics operations that conventional databases are grappling with. Aggregations, sorting, and grouping operations are intensive workloads for the CPU but can operate in parallel to the GPU database.
The global GPU Database market revenue is projected to reach close to USD 1,481.1 Million by 2028. The key drivers driving the GPU Database market include significant data generation through the BFSI, banking, media, and entertainment sectors. In addition to this, the massive usage of GPU databases for the GRC, fraud detection & avoidance, threat intelligence, SCM, and CEM are expected to spur industry trends for the GPU Database in the coming years. The massive popularity of GPU accelerated databases and tools in banks, insurance agencies, and many other financial institutions will make a huge contribution to GPU Database market revenue in the forthcoming years.
However, the lack of adequate technological competence and domain knowledge is likely to hamper the market growth. Furthermore, the increasing preference of enterprises toward AI and machine learning-enabled workloads is anticipated to be an opportunity for the GPU Database market.
Key Segments of the Global GPU Database Market
Component Overview, 2018-2028 (USD Million)
Deployment Overview, 2018-2028 (USD Million)
Application Overview, 2018-2028 (USD Million)
Industry Vertical Overview, 2018-2028 (USD Million)
Regional Overview, 2018-2028 (USD Million)
North America
Europe
Asia Pacific
Middle East and Africa
South America
Reasons for the study
What does the report include?
Who should buy this report?
A Graphics Processing Unit (GPU) is a single-chip processor that is often used to control and improve the performance of video and graphics. GPU is not only found on a video card or motherboard PC but is also used on smartphones, adapters, displays, workstations, and gaming consoles. GPUs are increasing exponentially to accelerate high performance for parallel data computing. Significant use of GPU databases for GRC, threat intelligence, fraud detection & prevention, and CEM is expected to push industry trends for GPU Database in the coming years. Besides, with the introduction of a supercomputer, demand for a GPU database is gaining traction around the world for successful data processing and reliable performance. However, a lack of awareness of the benefits of the GPU database limits business development owing to the failure of the embedded GPU to promote intensive graphic design software.
Component Segment
In terms of components, the market is bifurcated into tools and services. The tools segment further segment into In GPU-accelerated databases, and GPU-accelerated analytics. In the year 2020, the tools hold the largest market share and it is likely to keep its position throughout the forecast years. This is primarily due to the high-performance computing capabilities of GPU-accelerated databases that expand their distribution across diverse business applications. The need for technologies to handle intense analytics workloads without cost-effective companies is also required to build an appetite for GPU-accelerated analytics solutions thereby boosting the market growth.
Deployment Segment
In terms of deployment, the market is bifurcated into on-premises and cloud. The on-premises segment is expected to record the highest CAGR during the forecast period. On-premises deployment of a GPU database solution helps companies to own their records, comply with external regulatory criteria, and handle risks. . The growth of the on-premises deployment model is mainly due to the ability to tailor solutions as per dynamic enterprise needs, data protection, and privacy.
Application Segment
Based on the application segment, the market is segmented into governance, risk, and compliance, customer experience management, threat intelligence, fraud detection and prevention, predictive maintenance, supply chain management, and others. The customer experience management segment leads the market growth in 2020 and it is anticipated to hold its position during the forecast years. The market growth of this segment is mainly attributed to the growing need for real-time insights into customer data and service chain performance.
Industry Vertical Segment
In terms of the industry vertical segment, the market is segmented into BFSI, retail and eCommerce, healthcare and pharmaceuticals, telecommunications and it, transportation and logistics, government and defense, and others. In 2019, the BFSI segment accumulated the major market share and it is expected to do so over the forecast years. The BFSI vertical, consisting of banks, financial institutions, and insurance providers, are the leading adaptors of GPU-accelerated tools. This vertical generates a huge amount of data and has adopted advanced data analytics supercomputers since the launch of high-performance computing technology.
The North America region dominated the overall market in 2019 and it is projected to keep its position during the forecast years 2021-2028. However, the Asia-Pacific region is anticipated to gather the highest growth over the forecast years. The market growth in this region is mostly ascribed to the significant use of weather forecasting supercomputers and massive use of new technology in banking sectors in countries like India, Japan, and China, along with an increasing need for stable solutions in a multitude of financial institutions across these emerging economies.
The major players of the global GPU database market are Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB, Zilliz, and Jedox. Moreover, the market comprises several other prominent players in the GPU database market that are HeteroDB, H2O.ai, FASTDATA.io, Fuzzy Logix, and Anaconda. The GPU database market consists of well-established global as well as local players. Also, the previously recognized market players are coming up with new and advanced strategic solutions and services to stay competitive in the global market.
GPU database processes huge data volumes quicker and more effectively than CPUs because they operate in parallel instead of in sequence. GPUs speed up location-based and in-memory analysis, machine learning, and AI. With thousands of computing cores readily accessible on a single card, it is possible to execute functions in parallel, using brute force to solve complex analytics operations that conventional databases are grappling with. Aggregations, sorting, and grouping operations are intensive workloads for the CPU but can operate in parallel to the GPU database.
The global GPU Database market revenue is projected to reach close to USD 1,481.1 Million by 2028. The key drivers driving the GPU Database market include significant data generation through the BFSI, banking, media, and entertainment sectors. In addition to this, the massive usage of GPU databases for the GRC, fraud detection & avoidance, threat intelligence, SCM, and CEM are expected to spur industry trends for the GPU Database in the coming years. The massive popularity of GPU accelerated databases and tools in banks, insurance agencies, and many other financial institutions will make a huge contribution to GPU Database market revenue in the forthcoming years.
However, the lack of adequate technological competence and domain knowledge is likely to hamper the market growth. Furthermore, the increasing preference of enterprises toward AI and machine learning-enabled workloads is anticipated to be an opportunity for the GPU Database market.
Key Segments of the Global GPU Database Market
Component Overview, 2018-2028 (USD Million)
Deployment Overview, 2018-2028 (USD Million)
Application Overview, 2018-2028 (USD Million)
Industry Vertical Overview, 2018-2028 (USD Million)
Regional Overview, 2018-2028 (USD Million)
North America
Europe
Asia Pacific
Middle East and Africa
South America
Reasons for the study
What does the report include?
Who should buy this report?
Chapter 1 Introduction
1.1 Introduction to the Study
1.2 Market Definition and Scope
1.3 Units, Currency, Conversions, and Years Considered
1.4 Key Stakeholders
1.5 Key Questions Answered
Chapter 2 Research Methodology
2.1 Introduction
2.2 Data Capture Sources
2.2.1 Primary Sources
2.2.2 Secondary Sources
2.3 Market Size Estimation
2.4 Market Forecast
2.5 Data Triangulation
2.6 Assumptions and Limitations
Chapter 3 Executive Summary
Chapter 4 Market Outlook
4.1 Introduction
4.2 Value Chain Analysis
4.3 Market Dynamics
4.3.1 Drivers
4.3.1.1 Immense use of GPU database for GRC, fraud identification & prevention
4.3.1.2 Accessibility of Open Source Solutions and Their Growing Applications Areas
4.3.2 Restraints
4.3.2.1 Lack of Technical Expertise and Domain Knowledge
4.3.2.2 Opportunities
4.3.3.1 Increasing Preference of Enterprises toward AI and Machine Learning Facilitated Workloads
4.4 Porter’s Five Forces Analysis
4.5 PEST Analysis
4.6 COVID-19 Impact Analysis
Chapter 5 GPU database Market by Component
5.1 Introduction
5.1.1 Tools
5.1.1.1 GPU-Accelerated Databases
5.1.1.2 GPU-Accelerated Analytics
5.1.2 Services
Chapter 6 GPU database Market by Deployment Mode
6.1 Introduction
6.1.1 on Premise
6.1.2 Cloud
Chapter 7 GPU database Market by Application
7.1.1 Governance, Risk, and Compliance
7.1.2 Customer Experience Management
7.1.3 Threat Intelligence
7.1.4 Fraud Detection and Prevention
7.1.5 Predictive Maintenance
7.1.6 Supply Chain Management
7.1.7 Others
Chapter 8 GPU database Market by Industry Vertical
8.1 Introduction
8.1.1 BFSI
8.1.2 Retail and Ecommerce
8.1.3 Healthcare and Pharmaceuticals
8.1.4 Telecommunications and IT
8.1.5 Transportation and Logistics
8.1.6 Government and Defense
8.1.8 Others
Chapter 9 GPU database Market By Region
9.1 Introduction
9.2 North America
9.2.1 U.S.
9.2.2 Canada
9.3 Europe
9.3.1 Germany
9.3.2 France
9.3.3 UK
9.3.4 Rest of Europe
9.4 Asia Pacific
9.4.1 China
9.4.2 Japan
9.4.3 India
9.4.4 Rest of Asia Pacific
9.5 Middle East & Africa
9.5.1 UAE
9.5.2 South Africa
9.5.3 Rest of Middle East & Africa
9.6 South America
9.6.1 Brazil
9.6.2 Rest of South America
Chapter 10 Competitive Landscape
10.1 Overview
10.2 Strategic Initiatives
10.2.1 Mergers & Acquisitions
10.2.2 New Product Launch
10.2.3 Investments
10.2.4 Expansion
10.2.5 Customer Targeting
Chapter 11 Company Profiles
11.1 Kinetica
11.1.1 Overview
11.1.2 Products and Services Portfolio
11.1.3 Recent Initiatives
11.1.4 Company Financials
11.1.5 SWOT
11.2 OmniSci
11.2.1 Overview
11.2.2 Products and Services Portfolio
11.2.3 Recent Initiatives
11.2.4 Company Financials
11.2.5 SWOT
11.3 SQream
11.3.1 Overview
11.3.2 Products and Services Portfolio
11.3.3 Recent Initiatives
11.3.4 Company Financials
11.3.5 SWOT
11.4 Neo4j
11.4.1 Overview
11.4.2 Products and Services Portfolio
11.4.3 Recent Initiatives
11.4.4 Company Financials
11.4.5 SWOT
11.5 NVIDIA
11.5.1 Overview
11.5.2 Products and Services Portfolio
11.5.3 Recent Initiatives
11.5.4 Company Financials
11.5.5 SWOT
11.6 Brytlyt
11.6.1 Overview
11.6.2 Products and Services Portfolio
11.6.3 Recent Initiatives
11.6.4 Company Financials
11.6.5 SWOT
11.7 Blazegraph
11.7.1 Overview
11.7.2 Products and Services Portfolio
11.7.3 Recent Initiatives
11.7.4 Company Financials
11.7.5 SWOT
11.8 BlazingDB
11.8.1 Overview
11.8.2 Products and Services Portfolio
11.8.3 Recent Initiatives
11.8.4 Company Financials
11.8.5 SWOT
11.9 Zilliz
11.9.1 Overview
11.9.2 Products and Services Portfolio
11.9.3 Recent Initiatives
11.9.4 Company Financials
11.9.5 SWOT
11.10 Jedox
11.10.1 Overview
11.10.2 Products and Services Portfolio
11.10.3 Recent Initiatives
11.10.4 Company Financials
11.10.5 SWOT
11.11 Other Companies