GPU Database Market by Type, Application, Growth and Analysis – 2027


A New Market Study, titled “GPU Database Market Upcoming Trends, Growth Drivers and Challenges” has been featured on Market Research Future.

Market Synopsis

Market Research Future (MRFR) reveals different parameters that can contribute to the rise of the Global GPU database market 2020, across the analysis period. As per MRFR evaluation, the GPU database market can 19.28% CAGR across the year to come. From 2017 to 2023, the GPU database market can value from USD 195.3 million to USD 562.3 million. A complete assessment on the GPU market dynamics under the pandemic is also supplemented with the report. 

The increase in volume of data generation is creating high need for better performing computing applications, which is boosting the adoption for GPU (graphics processing unit) database. The increased application of GPU database can impel its marker in the years to come. The growing need for highly effective programmable processor that can offer high resolution videos and images, features that are offered by GPU, can also boost the expansion of the GPU database market in the near future. The ability of GPUs to processes enormous data in limited span is highly beneficial in IT sectors. The surge in the adoption of GPU database by cash-rich IT sector can promote the expansion of the GPU databases market in the analysis period. The rise in the awareness about high performance database operations can impel the expansion of the market in the near future. The rise in the adoption of technically advanced GPU, mostly backed by big data, machine learning, and artificial intelligence (AI) can impel the expansion of the market in the years to come.

Market Segmentation

The segment assessment of the GPU database market is done by deployment and component. 

The component based segment of the GPU database market are tools and services. The tools segments are GPU-accelerated analytics and GPU-accelerated databases. The services segments are support and maintenance services, and consulting services.

The deployment based segments of the GPU database market are cloud and on-premise. The application based segments of the GPU database market are risk, governance, compliance, customer experience management, threat intelligence, predictive maintenance, fraud detection and prevention, and supply chain management among others. 

The vertical based segments of the GPU database market are healthcare, BFSI, retail and ecommerce, government, aerospace and defense, transportation and logistics, and IT and telecommunications among others.

Regional Analysis

Trends of the global market for GPU database is studied across EU, APAC, MEA, and North America for the forecast period from 2018 to 2023. North America GPU database market is expected to thrive in the coming years. The regional market is expected to earn high revenue over other regions across the study period. The rising demand for data and the availability of machine learning and artificial intelligence solutions can impel the expansion of the regional market in the years to come. Omnisci, Nvidia, and Kinetica are some regional players that are likely to contribute significantly to the expansion of the market. EU GPU database market can rise at a high CAGR in the forecast period due to the increased demand for customer experience management in the years to come. In Asia Pacific, the GPU database market value is expected to rise. 

Key Players

Fuzzy Logix Inc. (US),  Kinetica DB Inc. (US), Nvidia Corporation (US), OmniSci, Inc. (US), Brytlyt (UK), Neo4j, Inc. (US), BlazingDB, Inc. (US), Jedox AG (Germany), Zilliz (China), SQream (US), HeteroDB, Inc. (Japan), Blazegraph (US), (US), (US), and Graphistry (US), among others are some prominent companies that are operating in the GPU database market as listed by MRFR. These players are shortlisted by regional presence, recent key developments, industry expertise, and product diversification.

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Major Key Points in Table of Content

1 Executive Summary
2 Scope Of The Report
2.1 Market Definition
2.2 Scope Of The Study
2.3 Research Objectives
2.4 Markets Structure


13 Company Profiles
13.1 Nvidia Corporation
13.1.1 Company Overview
13.1.2 Product/Business Segment Overview
13.1.3 Financial Updates
13.1.4 Key Developments
13.1.5 SWOT Analysis
13.1.6 Key Strategy
13.2 Kinetica DB Inc.
13.2.1 Company Overview
13.2.2 Product/Business Segment Overview
13.2.3 Financial Updates
13.2.4 Key Developments
13.2.5 SWOT Analysis
13.2.6 Key Strategy
13.3 OmniSci, Inc.
13.3.1 Company Overview
13.3.2 Product/Business Segment Overview
13.3.3 Financial Updates
13.3.4 Key Developments
13.3.5 SWOT Analysis
13.3.6 Key Strategy
13.4 Neo4j, Inc.
13.4.1 Company Overview
13.4.2 Product/Business Segment Overview
13.4.3 Financial Updates
13.4.4 Key Developments
13.4.5 SWOT Analysis
13.4.6 Key Strategy
13.5 Brytlyt
13.5.1 Company Overview
13.5.2 Product/Business Segment Overview
13.5.3 Financial Updates
13.5.4 Key Developments
13.5.5 SWOT Analysis
13.5.6 Key Strategy
13.6 BlazingDB, Inc.
13.6.1 Company Overview
13.6.2 Product/Business Segment Overview
13.6.3 Financial Updates
13.6.4 Key Developments
13.6.5 SWOT Analysis
13.6.6 Key Strategy
13.7 Zilliz
13.8 SQream
13.9 Jedox AG
13.10 HeteroDB, Inc.


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