In-memory computing is middleware allowing one to store data in a cluster of computers and run other processes in parallel. Shift to dynamic RAM and increasing number of processes can drive the market demand. Market Research Future’s (MRFR) report on the in-memory computing market covers projections for growth and revenue for the forecast period (2020-2027). The COVID-19 outbreak and its ability to impact revenues of the industry have been explored in the report.
The global in-memory computing market is poised to exhibit 19% CAGR from 2017 to 2023. It is driven by huge data generated by verticals of gaming and entertainment, BFSI, and telecommunication coupled with replacement of disk-based data management systems. Implementation of in-memory data grid (IMDG) platforms for handling volume, variety, and velocity of data will boost market growth.
Rise of AI and ML can offer new insights in real-time. Capture of customer-agent interactions for valuable insights and optimizing outcomes through data discovery platforms can drive the in-memory computing market growth. Successful use cases in healthcare, retail, and BFSI can propel market growth.
But lack of skilled personnel and paucity of standards in architectures can hamper market growth.
COVID-19 Impact Analysis
The COVID-19 outbreak has severely affected the IT spending of various companies and affected market growth. Slowdown of businesses and changes in customer behavior can affect market. However, demand for machine learning and artificial intelligence to tackle challenges caused by the pandemic can have a positive impact on the market. Modernization of cloud and rise of work-from-home policies coupled with management of large datasets by various verticals can bolster market demand.
Get a Free Sample @ https://www.marketresearchfuture.com/sample_request/10383
By component, the in-memory computing market has been segmented into solutions and services. The solution segment is further segmented into in-memory data grid (IMDG), in-memory database (IMDB), and data stream processing. The in-memory database (IMDB) segment is further sub-classified into online analytical processing (OLAP) and online transaction processing (OLTP). Services are managed services and professional services. The professional services segment is sub-segmented into system integration and implementation, consulting, support, and maintenance. Among components, the services segment can lead in the market owing to need for consulting and technical support services. Resolution of pre and post-deployment queries and planning of new strategies through adoption, training, and implementation can drive the segment growth.
Major applications of the in-memory computing market are predictive analysis, supply chain management, sales and marketing optimization, risk management and fraud detection, sentiment analysis, geospatial/GIS processing, and others. The other segment is sub-segmented into claim processing and modeling, image processing, route optimization, and trade promotion simulations. The predictive analysis application is poised to dominate the market owing to deliverance of consistent customer service at every touchpoint.
On the basis of deployment mode, the in-memory computing market has been segmented into cloud and on-premises.
By organization size, the in-memory computing market has been segmented into SMEs and large enterprises.
Based on vertical, the in-memory computing market has been segmented into healthcare & life sciences, BFSI, IT & telecom, transportation & logistics, retail & e-commerce, government & defense, energy & utilities, media & entertainment, and others. The ’others’ segment is sub-segmented into manufacturing, education, and travel & hospitality.
The Middle East & Africa (MEA), North America, Europe, Asia-Pacific, and Latin America are major regions covered in the in-memory computing market.
North America is expected to lead the in-memory computing market due to demand for analytics platforms for small and medium enterprises. Presence of reputed vendors such as Oracle coupled with demand for enhanced customer services.
SAS Institute, Enea, Fujitsu, Microsoft, Teradata, Red Hat, Hazelcast, IBM, Altibase, Salesforce, SAP, Kognitio, Exasol, GridGain, TIBCO, GigaSpaces, Workday, Software AG, McObject, MemSQL, Oracle, Qlik, MongoDB, VoltDB, and Intel are key players of the in-memory computing market.
GridGain Systems has launched Expert on Call, a service for application developers and architects to resolve any queries pertaining to in-memory computing.
Browse Complete Report @ https://www.marketresearchfuture.com/reports/in-memory-computing-market-10383
In-Memory Computing Market Research Report: Information By Component (Solutions (In-Memory Database (IMDB), (Online Analytical Processing (OLAP), Online Transaction Processing)(OLTP)), In-Memory Data Grid (IMDG) and Data Stream Processing), Services (Professional Services (Consulting, System Integration and Implementation, Support and Maintenance), Managed Services)), Application (Risk Management and Fraud Detection, Sentiment Analysis, Geospatial/GIS Processing, Sales and Marketing Optimization, Predictive Analysis, Supply Chain Management, Others (Image Processing, Route Optimization, Claim Processing and Modelling and Trade Promotion Simulations)), Deployment Mode (Cloud and On-Premises), Organization Size (SMEs and Large Enterprises), Vertical (BFSI, IT & Telecom, Retail & eCommerce, Healthcare & Life Sciences, Transportation & Logistics, Government & Defense, Energy & Utilities, Media & Entertainment, Others (Education, Manufacturing and Travel & Hospitality)) – Forecast till 2027