GPU database Market is projected to grow up to USD 697.4 million by 2027 growing at a CAGR of 30.5% during the forecasting period 2021-2027.

The GPU, or graphics processing unit, is a programmable processor that enables us to create high-definition pictures and movies. GPUs have the ability to process huge amounts of data in parallel, allowing them to manage large amounts of data in much less time. GPU databases make advantage of graphics processing units (GPUs) to perform database operations. Deep learning, artificial intelligence (AI), and big data are all applications for them. Deep teaching strategies do not need CPUs since they demand many cores to perform concurrent fundamental computations, which seem to be prohibitively expensive on a single processor.
GPU databases can handle huge quantities of data more quicker and more effectively than CPU databases because they operate in parallel rather than in sequence. GPUs accelerate location-based and in-memory analytics, machine learning, and artificial intelligence (AI). With thousands of processing cores readily accessible on a single card, it is feasible to execute tasks in parallel, using brute force to solve complicated analytical processes that are difficult for conventional databases to handle. Aggregations, sorts, and grouping operations are time-consuming activities for a CPU, but they may be performed efficiently in parallel on a GPU database.
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The GPU database Market report has been categorized as below:
Based on applications
GRC
Threat Intelligence
CEM
Fraud Detection and Prevention
Predictive Maintenance
SCM
Others
Based on components
Tools
GPU-accelerated Databases
GPU-accelerated Analytics
Services
Based on deployment
On-premises
Cloud
Based on verticals
BFSI
Retail and eCommerce
Healthcare and Pharmaceuticals
Telecommunications and IT
Transportation and Logistics
Government and Defense
Others
By Region
North America
Europe
Asia Pacific
Rest of World
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