January 8 2021
The in-memory computing market is substantially influenced due to the increasing pandemic situation of COVID-19 across the world. The COVID-19 pandemic has had a major impact on the global economy. The in-memory computing market is anticipated to grow significantly due to the increasing need for rapid data processing and the explosion of big data across various verticals.
Global In-Memory Computing Market is expected to perceive a decent rise in income in the upcoming period. In this report, Market Research Future (MRFR) includes the segmentation and dynamics of the market to offer a better glimpse of the coming years.
The key players of the global in-memory computing market are IBM (US), SAS Institute (US), TIBCO (US), Software AG (Germany), Intel (Germany), Qlik (US), Red Hat (US), Altibase (US), GigaSpaces (US), Teradata (US), Kognitio (UK), Salesforce (US), Workday (US), Enea (Sweden), Microsoft (US), Oracle (US), Hazelcast (US), MongoDB (US), Exasol (Germany), SAP (Germany), Fujitsu (Japan), GridGain (US), VoltDB (US), McObject (US), and MemSQL (US).
Global In-Memory Computing Market has been segmented based on Component, Application, Deployment Mode, Organization Size, Vertical, and Region.
Based on component, the in-memory computing market has been segmented into solutions and services. The solution segment is further divided into in-memory database (IMDB), in-memory data grid (IMDG), and data stream processing. The IMDB segment held the largest market share of the global in-memory computing market and is also expected to witness the highest CAGR during the forecast period. IMDB keeps the whole dataset in RAM instead of a disk drive to produce quicker response times. The in-memory database (IMDB) segment is further sub-classified into online analytical processing (OLAP) and online transaction processing (OLTP).
Based on application, the in-memory computing market has been segmented into sentiment analysis, geospatial/GIS processing, sales and marketing optimization, predictive analysis, risk management and fraud detection, supply chain management, and others. The risk management and fraud detection segment is expected to account for the highest market share during the forecast period. The highest market share of the risk management and fraud detection segment is accredited to a growing focus on enhancing risk intelligence capabilities to fight risk exposures.
Based on deployment mode, the in-memory computing market has been segmented into cloud and on-premises. The cloud segment is likely to have a larger market share in the in-memory computing market during the forecast period. This is mainly due to the cloud database solution that provides scalability, speed, and flexibility. It enables security, privacy, and anonymization with enterprise reliability
Based on organization size, the in-memory computing market has been segmented into SMEs, large enterprises. The SMEs segment held the larger market share of the global in-memory computing market. Increasing demand for big data and the growing number of SMEs drive the growth of the small and mid-size enterprises segment.
Based on vertical, the in-memory computing market has been segmented into BFSI, IT and telecom, retail and e-commerce, healthcare and life sciences, transportation and logistics, government and defense, energy and utilities, media and entertainment, and others. The BFSI segment accounted for the largest market share of the global in-memory computing market and is also expected to witness the highest CAGR during the study period owing to the increasing usage of mobile and Internet banking.
The regional analysis for the in-memory computing has been done for North America, Europe, Asia-Pacific, and the Middle East & Africa, and South America. The market in North America accounted for the largest share in 2019, and it is expected to register strong growth during the forecast period. The market in Asia-Pacific is expected to register the highest CAGR during the forecast period. This growth can be attributed to the increasing adoption of cloud and IoT and increasing use of the web.