WILMINGTON, DE, UNITED STATES, February 1, 2024 /EINPresswire.com/ -- According to a recent report published by Allied Market Research, titled, " In-Memory Analytics Market Share by Component, Deployment Model, Organization Size, Application, and Industry Vertical: Global Opportunity Analysis and Industry Forecast, 2019-2026,"
The global In-Memory analytics market revenue was valued at $1.956 billion in 2018, and is projected to reach $11.858 billion by 2026, growing at a CAGR of 25.40% from 2019 to 2026.
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In-memory analytics helps organization to improve the overall speed in the BI system and provide different business intelligence clients with quicker solutions as compared to traditional disk based BI systems, especially for queries that take a long time to process in a large database. Furthermore, rise in need for self-service business intelligence and advanced technologies are the major factors that drive the growth of the market. Numerous benefits associated with in-memory analytics include real-time insights, fast processing, and safety & security features provided to the organizations data.
Furthermore, digital transformation using real-time analytics and increase in volume of data are the major factors that boost the growth of the market. In addition, surge in trends for self-service BI tools and technological advancement in computing power are the factors that fuel the growth of the market. However, lack of awareness among various industry verticals is expected to impede the market growth. Furthermore, improved scalability and security with cloud-based in-memory analytics and higher adoption by SMEs are expected to present major opportunities for the expansion of the market in future.
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Competitive Analysis:
The competitive environment of In-Memory Analytics Industry is further examined in the report. It includes details about the key players in the market's strengths, product portfolio, In-Memory Analytics Market share and size analysis, operational results, and market positioning. It comprises the actions taken by the players to grow and expand their presence through agreements and entering new business sectors. Mergers and acquisitions, joint ventures, and product launches are some of the other techniques used by players.
Key Players:
Amazon Web Services, Inc.
SAP SE
Oracle Corporation
SAS Institute Inc.
International Business Corporation
Hitachi, Ltd.
Software AG
MicroStrategy Incorporated
Qlik Technologies
Kognito Ltd and Many More
Region wise, the global in-memory analytics market was dominated by North America in 2018 and is expected to maintain this trend during the forecast period. The major factors that drive the growth of the market in this region include increase in demand for in-memory database system for quick storage and fast transfer of files, presence of major market players, and technical expertise in this region. However, Asia-Pacific is expected to witness highest growth rate during the forecast period, owing to adoption of in-memory analytics by various SMEs for managing huge quantity of data.
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The sale & marketing optimization segment dominated the in-memory analytics market industry in 2018 and is projected to maintain its dominance during the forecast period, owing to its adoption by many companies for understanding the requirements of the customers. Furthermore, predictive asset management segment is expected to grow at a significant CAGR during the forecast period, owing to its adoption by organizations for analyzing historical and real-time data from various sites for helping them predict the excepted failures before it happens.
The BFSI sector dominated the in-memory analytics market industry in 2018 and is projected to maintain its dominance during the forecast period, owing to its adoption in various banking and financial institution to improve customer service and satisfaction, to enter new markets, and to establish data exchange. Furthermore, the IT & telecom sector is expected to grow at a significant CAGR during the forecast period, owing to its adoption for gaining customer insights as well as product performance insights from huge quantity of data.
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