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In-memory Data Grid Market

In-memory Data Grid Market

Size, Share, Competitive Landscape and Trend Analysis Report by Component (Solution, Service), by Deployment Mode (On-Premise, Cloud), by Enterprise Size (Large Enterprises, Small and Medium-Sized Enterprises (SMEs)), by Application (Transaction Processing, Fraud and Risk Management, Supply Chain Optimization, Sales and Marketing Optimization) and by Industry Vertical (BFSI, Media and Entertainment, Consumer Goods and Retail, Healthcare and Life Sciences, Manufacturing, IT and Telecom, Transportation and Logistics, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032

Report Code: A09783
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In-memory Data Grid Market Insight

An in-memory data grid (IMDG) is a customary of clustered or networked computers that combine their random-access memory to stakeinformation with other applications successively in the cluster.  It stores large amount of data and distributes in-memory data store. IMDGs are built for data processing at extremely high speeds and designed for running and building large-scale applications that are essential more RAM, which exists in a single computer server. This allows the highest application presentation by consuming RAM along with the handling power of multiple computers. IMDGs are especially useful for big parallel handling applications on huge data sets.

Impact of COVID-19 on In-memory Data Grid Market:

  • Since the COVID-19 virus outbreak in December 2019, the disease has spread to almost all countries around the globe, with the WHO declaring it a public health emergency. The global impacts of the disease are already starting to be felt, and expected to significantly affect the global in-memory data grid market in 2020.
  • Using better AI model can help companies to reduce operating costs and increased customer satisfaction by providing better services.
  • In-memory data grid tools also significantly help the retail segment by enhancing high-performance data management in transactional applications, such as retailer apps and shopping.
  • Overall, the pandemic is expected to have a positive impact on the in-memory data grid market.

Top impacting factors: Market scenario analysis, trends, drivers, and impact analysis

The factor influencing the market such as reducing the need for relational based data model and database is driving the growth ofin-memory data grid market. With the help of distributed architecture, organizations can enhance limited storage capacity of the main memory which save cost, driving the demand for in memory data grid market. Increasing technological progression in memory grid and its acceptance in business verticals is increasing the demand for in-memory data grid market. However, disappointment of systems or components results in loss of stored data which hinders the growth of the market. Contrarily, with the in-memory data grid organizations havereach high throughput with real-time handling and also progress the routine of analytical applications is driving the demand for in memory data grid market in the forecasted years.

Increasing demand for IMDG in industry verticals

IMDGs are used throughout a wide spectrum of vertical industries in applications as diverse as risk analytics, trading systems, bio informatics, eCommerce, or online gaming. Essentially every project that struggles with scalability and performance have benefits from in-memory processing and IMDG architecture, driving the demand for in memory data grid market.

Technology advancement in IMDG market

Recent development in IMDG is transactional ACID support. It involved 2-phase-commit (2PC) protocol that is used to confirm data consistency within cluster. Different IMDGs have dissimilaroriginalsecuringdevices, but usually more progressiveapplications will deliver concurrent securing mechanisms such as (MVCC) multi-version concurrency controland decrease network load to a least, hence assuring transactional ACID reliability with very high presentation. Dissimilar products deliver different 2PC optimizations, but generally the drive of all optimizations is to upsurge concurrency, minimize network overhead, and decrease the number of hairs a businessneeds to ample.

Key benefits of the report:

  • This study presents the analytical depiction of the global In-memory data gridindustry along with the current trends and future estimations to determine the imminent investment pockets.
  • The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the global In-memory data gridmarket share.
  • The current market is quantitatively analyzed to highlight the global In-memory data gridmarket growth scenario.
  • Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
  • The report provides a detailed global In-memory data gridmarket analysis depending on competitive intensity and how the competition will take shape in coming years.

In-memory Data Grid Market Report Highlights

Aspects Details
By Component
  • Solution
  • Service
By Deployment Mode
  • On-Premise
  • Cloud
By Enterprise Size
  • Large Enterprises
  • Small and Medium-Sized Enterprises (SMEs)
By Application
  • Transaction Processing
  • Fraud and Risk Management
  • Supply Chain Optimization
  • Sales and Marketing Optimization
By Industry Vertical
  • BFSI
  • Media and Entertainment
  • Consumer Goods and Retail
  • Healthcare and Life Sciences
  • Manufacturing
  • IT and Telecom
  • Transportation and Logistics
  • Others
By Region
  • North America  (U.S., Canada)
  • Europe  (France, Germany, Italy, Spain, UK, Rest of Europe)
  • Asia-Pacific  (China, Japan, India, South Korea, Australia, Rest of Asia-Pacific)
  • LAMEA  (Latin America, Middle East, Africa)
Key Market Players Alachisoft, Software AG, GigaSpaces Technologies Inc., IBM Corporation, Red Hat, Inc., Hazelcast IMDG, TIBCO Software Inc., ScaleOut Software, Oracle Corporation, GridGain Systems, Inc.

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