At 16.0% CAGR, the SAM GPU Database Market is projected to be worth US$ 39.57 million by 2028, says Business Market Insights              

According to Business Market Insights’ research, the SAM GPU database market was valued at US$ 16.20 million in 2022 and is expected to reach US$ 39.57 million by 2028, registering a CAGR of 16.0% from 2022 to 2028. Availability of open source solutions and growing applications areas and regulations creating demand for solutions providing performance-at-scale are the critical factors attributed to the market expansion.                

The growing trend for adopting open source GPU database solutions that deliver flexibility, high quality, considerably lower cost, and enhanced security for analytical applications is driving the market growth faster over the forecast period. Adopting specific GPU solutions enabling high Q performance for computing in a particular vertical range offer potential opportunities for adopting database solutions. To enable the running of AI and ML workloads for enterprise use cases, Nvidia released version 2.1 of its AI Enterprise software suite. In August 2021, Nvidia AI Enterprise became generally accessible as a collection of supported AI and ML solutions that function well on Nvidia’s hardware. Thus, the support for open source strengthened by Nvidia AI Enterprise 2.1 is further boosting the market growth. The growing application of GPU databases across various applications is driving the market. For instance, in February 2019, Uber introduced AresDB, an open-source real-time analytics engine leveraging an unconventional power source, graphics processing units (GPUs), to meet the growing demands of analysis at scale and simultaneously unifying, simplifying, and improving Uber's existing solutions. Also, in April 2021, Cloudera, an enterprise data cloud company, announced that Cloudera Data Platform (CDP) would integrate RAPIDS Accelerator into Apache Spark 3.0. Thus, such growing adoption across various applications is driving the market.

On the contrary, limited capabilities of available GPU databases to perform crucial operations in analytics use cases hurdles the growth of SAM GPU database market.    

Based on component, the SAM GPU database market is segmented into tool and services segment. The tool segment held 75.9% market share in 2022, amassing US$ 12.29 million. It is projected to garner US$ 28.94 million by 2028 to expand at 15.3% CAGR during 2022–2028.  

Based on deployment, the SAM GPU database market is segmented cloud based and on-premise. The on-premise segment held 64.6% market share in 2022, amassing US$ 10.46 million. It is projected to garner US$ 24.54 million by 2028 to expand at 15.3% CAGR during 2022–2028.

Based on application, the SAM GPU database market is segmented into fraud detection and prevention, governance risk & compliance (GRC), customer experience management, predictive maintenance, supply chain management, threat intelligence, and others. The customer experience management segment held 28.8% market share in 2022, amassing US$ 4.66 million. It is projected to garner US$ 12.10 million by 2028 to expand at 17.2% CAGR during 2022–2028.

Based on industry vertical, the SAM GPU database market is segmented into BFSI, IT & telecom, retail & e-commerce, healthcare, transportation & logistics, government & defense, and others. The IT & telecom segment held 26.1% market share in 2022, amassing US$ 4.23 million. It is projected to garner US$ 9.68 97 million by 2028 to expand at 14.8% CAGR during 2022–2028.

Based on country, the SAM GPU database market is segmented into Brazil, Argentina, and Rest of SAM. Our regional analysis states that Brazil captured 66.1% market share in 2022. It was assessed at US$ 10.72 million in 2022 and is likely to hit US$ 26.11 million by 2028, exhibiting a CAGR of 16.0% during the forecast period.    

Key players dominating the SAM GPU database market are Brytlyt; H2O.ai; Jedox; and Nvidia Corporation, among others. 

• In 2018, Kinetics formed a partnership with Dell EMC, has offered certain integrated solutions and developed certain database platforms for correlating the massive database units with digital things. Their joint venture creates datasets and certain actionable insights on combining their so manufactured hardware with a database along with a visualization engine.

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