CHICAGO, December 5, 2018
CHICAGO, December 5, 2018 /PRNewswire/ --
According to the new market research report "GPU Database Market by Application (GRC, Threat Intelligence, CEM, Fraud Detection and Prevention, SCM), Tools (GPU-accelerated Databases and GPU-accelerated Analytics), Deployment Model, Vertical, and Region - Global Forecast to 2023", published by MarketsandMarkets™, the global GPU Database Market size is expected to grow from USD 178 million in 2018 to USD 455 million by 2023, at a Compound Annual Growth Rate (CAGR) of 20.7% during the forecast period.
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The key factors driving the GPU Database Market include massive data generation across BFSI, retail, and media and entertainment industries.
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CEM application segment to hold the largest market size in 2018
GPU-accelerated databases with their brute force computing power can ingest vast amount of data related to customers from a variety of sources. Enterprises can analyze this data and gain real-time insights into their consumer's buying behavior, understand market dynamics and trends, forecast demand and supply, and identify service issues and performance bottlenecks in the service chain. This high-performance computing capability is crucial to customer-focused verticals, including retail and eCommerce, telecom, and BFSI, where customer experience can make a significant difference with the highly competitive environment.
Services segment to grow at a higher CAGR during the forecast period
The GPU Database Market by component has been segmented into tools and services. Training and consulting along with support and maintenance services enable organizations to maintain healthy consumer relationships. Additionally, the services also assist enterprises in maximizing their resource usage, effectively executing the activities enhancing business operations. The need for services, such as support and maintenance, would also grow, as the adoption of GPU database tools increases.
BFSI vertical to lead the adoption of GPU database during the forecast period
The BFSI vertical comprising banks, financial services, and insurance companies are the leading adopters of GPU-accelerated tools. This vertical generates huge amount of data and has adopted supercomputers for advanced data analytics since the inception of high-performance computing technology. GPU-accelerated tools, such as database and analytics find significance in interactive portfolio risk management, trade execution, customer analysis, and credit scoring applications. The advent of GPU-accelerated tools has simplified operations facilitating rapid data processing and real-time analytics. In the recent past, real-time risk management analytics is the major challenge for financial organizations. With the emergence of GPU-accelerated tools, organizations able to perform risk calculations and simulations in real time are using up-to-the-moment data. Parallel computing with the GPU applications enable organizations to monitor for anomalies in diverse streams of transactions and log data.
North America to hold the largest market size during the forecast period
North America is expected to account for the highest market share, due to the early adoption of GPU- accelerated tools as well as prominent initiatives taken by the industry players in the form of partnerships with different technology players to offer rapid analytics and data processing solutions. The major presence of GPU database vendors as well as the widespread awareness about these solutions would continue to help the region sustain its largest market share during the forecast period.
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Major vendors offering GPU database globally include Kinetica (US), OmniSci (US), SQream (US), Neo4j (US), NVIDIA (US), Brytlyt (UK), Blazegraph (US), BlazingDB (US), Zilliz (US), Jedox (Germany), HeteroDB (Japan), H2O.ai (US), FASTDATA.io (US), Fuzzy Logix (US), Anaconda (US), and Graphistry (US). The study includes an in-depth competitive analysis of the key players in the GPU Database Market, along with their company profiles, recent developments, and key market strategies.
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