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In-Memory Data Grid Market by Component, Business Application (Transaction Processing, Fraud and Risk Management, Supply Chain Optimization), Industry Vertical, Organization Size, Deployment Type, and Region - Global Forecast to 2023

  • ID: 4715565
  • Report
  • December 2018
  • Region: Global
  • 133 Pages
  • Markets and Markets
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Increasing Use of Distributed Architecture to Enhance Limited Storage Capacity of Main Memory to Drive the In-Memory Data Grid Market

FEATURED COMPANIES

  • Alachisoft
  • Gridgain Systems
  • Hitachi
  • Oracle
  • Red Hat
  • Software AG
  • MORE

Increasing use of distributed architecture to enhance limited storage capacity of main memory to drive the in-memory data grid market

The global in-memory data grid market size is expected to grow from USD 1.4 billion in 2018 to USD 2.3 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 10.8% during the forecast period. The in-memory data grid market is driven by various factors, such as the use of distributed architecture to enhance limited storage capacity of main memory, and focus on eliminating the need for relational data model and database. However, system or components failure which may result in loss of data, can hinder the growth of the market.

The fraud and risk management segment to grow at the highest CAGR during the forecast period

Organizations use fraud and risk management applications to enhance their risk intelligence capabilities to overcome risk exposures. Risk management has become a top focus for regulatory bodies around the world. It has increasingly become important for several businesses to provide accurate and timely risk reporting to regulatory agencies. Using in-memory data grid helps unify corporate risk data, perform the required analytics, and report relatively easy as compared to traditional methods of data management.

The BFSI vertical to hold the largest market size during the forecast period

Financial organizations across the globe are looking for in-memory data grid solutions which can process data in real time and improve the performance of their business-critical applications. Trading systems with high transaction rates are examples of environments best-suited for the in-memory data grid. It enables financial applications with real-time analytics due to faster data access and high throughput in use cases, such as trading, fraud detection, risk management, and portfolio management. Using in-memory data grid solution would enable financial organizations to improve their marketing strategies and customer retention policies, develop new investment strategies, and mitigate risks.

Asia Pacific (APAC) to record the highest growth rate during the forecast period

APAC is expected to grow at the highest CAGR during the forecast period, due to an increasing demand for in-memory data grid. Major APAC countries, such as China, Australia and New Zealand, India, and Singapore, provide significant opportunities for the adoption of the in-memory data grid solutions across industry verticals. Meanwhile, North America is projected to hold the largest market size during the forecast period.
In-depth interviews were conducted with Chief Executive Officers (CEOs), marketing directors, other innovation and technology directors, and executives from various key organizations operating in the in-memory data grid marketplace.

The following list provides the breakup of primary respondents’ profiles:

  • By company type: Tier 1 – 35%, Tier 2 – 45%, and Tier 3 – 20%
  • By designation: C-level – 35%, D-level – 25%, and Others – 40%
  • By region: North America – 40%, Europe – 30%, APAC – 20%, MEA – 5%, and Latin America – 5%

Major vendors offering in-memory data grid solutions across the globe include IBM (US), Oracle (US), Red Hat (US), Software AG (Germany), Pivotal (US), Hitachi (Japan), Hazelcast (US), TIBCO (US), GridGain (US), ScaleOut Software (US), GigaSpaces (US), Alachisoft (US), and TmaxSoft (US). The study includes an in-depth competitive analysis of these key players in the in-memory data grid market, with their company profiles, recent developments, and key market strategies.

Research Coverage
This research study covers the segmentation of the in-memory data grid market by component, business application, deployment type, organization size, industry vertical, and region. These segments are mapped across 5 major regions: North America, Europe, Asia Pacific, the Middle East and Africa and Latin America. The report provides in-depth market intelligence regarding key factors, such as drivers, opportunities, and challenges, influencing the growth of the in-memory data grid market across the globe. It also offers an analysis of micromarkets with respect to individual growth trends, prospects, and their contribution to the overall in-memory data grid market.

Key Benefits
The report will help the market leaders/new entrants in the market with information on the closest approximations of the revenue numbers for the overall in-memory data grid market and the subsegments. The report will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and to plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.

Note: Product cover images may vary from those shown
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FEATURED COMPANIES

  • Alachisoft
  • Gridgain Systems
  • Hitachi
  • Oracle
  • Red Hat
  • Software AG
  • MORE

1 Introduction
1.1 Objectives of the Study
1.2 Market Definition
1.3 Market Scope
1.4 Years Considered for the Study
1.5 Currency Considered
1.6 Stakeholders

2 Research Methodology
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakup of Primary Profiles
2.1.2.2 Key Industry Insights
2.2 Market Breakup and Data Triangulation
2.3 Market Size Estimation
2.3.1 Bottom-Up Approach
2.3.2 Top-Down Approach
2.4 Assumptions for the Study
2.5 Limitations of the Study

3 Executive Summary

4 Premium Insights
4.1 Attractive Market Opportunities in the In Memory Data Grid Market
4.2 Market By Business Application and Country (2018)
4.3 Market Major Countries

5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Using Distributed Architecture to Enhance Limited Storage Capacity of the Main Memory
5.2.1.2 Eliminating the Need for Relational Data Model and Database
5.2.2 Restraints
5.2.2.1 System/Component Failure May Result in the Loss of Data
5.2.3 Opportunities
5.2.3.1 Attaining High Throughput With Real-Time Processing
5.2.3.2 Improving the Performance of Analytical Applications
5.2.4 Challenges
5.2.4.1 Maintaining Data Security
5.3 Industry Trends
5.3.1 Use Case 1: Pivotal Software
5.3.2 Use Case 2: Hazelcast
5.3.2.1 Use Case 3: Tibco Software

6 In Memory Data Grid Market, By Component
6.1 Introduction
6.2 Solution
6.2.1 Growing Need to Have Streamlined and High-Performing Applications to Drive the Adoption of the In-Memory Data Grid Solution Among Enterprises
6.3 Professional Services
6.3.1 Consulting
6.3.1.1 Growing Need Among Organizations to Be Technically Well Versed to Drive the Growth of In-Memory Data Grid Consulting Services
6.3.2 Support and Maintenance
6.3.2.1 Focus on Improving the Performance of Applications to Drive the Growth of In-Memory Data Grid Support and Maintenance Services
6.3.3 Education
6.3.3.1 Need to Educate Employees on How to Use In-Memory Data Grid Solutions to Drive the Adoption of In-Memory Data Grid Educational Services

7 In Memory Data Grid Market, By Business Application
7.1 Introduction
7.2 Transaction Processing
7.2.1 Growing Need for Faster and Smoother Transactions to Drive the Adoption of In-Memory Data Grid in the Transaction Processing Business Application
7.3 Fraud and Risk Management
7.3.1 Regulatory Compliances Among Organizations to Boost the Adoption of In-Memory Data Grid in the Fraud and Risk Management Business Application
7.4 Supply Chain Optimization
7.4.1 Growing Need for Handling Large Datasets to Drive the Adoption of In-Memory Data Grid in the Supply Chain Optimization Business Application
7.5 Sales and Marketing Optimization
7.5.1 Adopting In-Memory Data Grid for Analyzing Customer Data to Improve Sales and Marketing Operations

8 In Memory Data Grid Market, By Industry Vertical
8.1 Introduction
8.2 Banking, Financial Services, and Insurance
8.2.1 Demand for Real-Time Analysis of Data Generated From Financial Applications to Drive the Growth of the Market
8.3 Media and Entertainment
8.3.1 Growing Focus of Organizations to Deliver Quality Content at Fast Pace to Drive the Growth of the Market
8.4 Consumer Goods and Retail
8.4.1 Driving Sales By Improving Operational Efficiencies to Drive the Growth of the Market
8.5 Healthcare and Life Sciences
8.5.1 Demand for Proactive Diagnostic Services to Enhance Patient Experience to Drive the Growth of the Market
8.6 Manufacturing
8.6.1 Increasing Need for Real-Time Production Planning and Demand Forecasting to Drive the Growth of the Grid Market
8.7 Telecom and It
8.7.1 Growing Need for Organizations to Cater Dynamic Customer Preferences to Drive the Growth of the Market
8.8 Transportation and Logistics
8.8.1 Demand From Organizations for Accurate Information to Make Better Business Decisions to Drive the Growth of the Market
8.9 Others

9 In Memory Data Grid Market, By Organization Size
9.1 Introduction
9.2 Large Enterprises
9.2.1 Demand for High-Performance Computing to Drive the Growth of the Market
9.3 Small and Medium-Sized Enterprises
9.3.1 Need for Cost-Effective Solutions Offering High Scalability and Enhanced System Performance to Drive the Growth of Market

10 In Memory Data Grid Market, By Deployment Type
10.1 Introduction
10.2 On-Premises
10.2.1 Security Concerns Among Enterprises to Drive the Adoption of the On-Premises In-Memory Data Grid Solution
10.3 Cloud
10.3.1 Scalability and Cost-Effectiveness are the Major Advantages to Adopt A Cloud-Based In-Memory Data Grid Solution

11 In Memory Data Grid Market, By Region
11.1 Introduction
11.2 North America
11.2.1 United States
11.2.1.1 Early Adoption of Technology and Strong R&D Investments to Boost the Growth of the US In-Memory Data Grid Industry
11.2.2 Canada
11.2.2.1 Growing Demand for the Analytical-Based Solutions to Drive the Growth of the Market in Canada
11.3 Europe
11.3.1 United Kingdom
11.3.1.1 Increasing Focus of Organizations to Effectively Handle Large Data Volumes Leads to the Growth of the UK In-Memory Data Grid Industry
11.3.2 Germany
11.3.2.1 Demand for High Technological Solutions to Drive the Growth of Germany In-Memory Data Grid Industry
11.3.3 France
11.3.3.1 Increasing Investments of Organizations in Real-Time Analytics Solutions Leads to the Growth of the Market in France
11.3.4 Rest of Europe
11.4 Asia Pacific
11.4.1 China
11.4.1.1 Increasing Data Volumes Across Industry Verticals to Contribute to the Growth of the Market in China
11.4.2 Japan
11.4.2.1 Rise in the Adoption of Connected Devices to Contribute to the Growth of the Market in Japan
11.4.3 Australia and New Zealand
11.4.3.1 Growing Need to Offer Personalized Products and Services Leads to the Growth of the Market in Australia and New Zealand
11.4.4 Rest of Asia Pacific
11.5 Middle East and Africa
11.5.1 Kingdom of Saudi Arabia
11.5.1.1 Increasing Adoption of Advanced It Infrastructure in the Energy and Utilities Industry Vertical to Contribute to the Growth of the Market in Ksa
11.5.2 United Arab Emirates
11.5.2.1 State-Of-The-Art Infrastructure and the Implementation of the Cutting-Edge Technology Lead to the Growth of the In Memory Data Grid Market in the UAE
11.5.3 South Africa
11.5.3.1 Increasing Adoption of In-Memory Computing Technologies to Spur the Demand for the Market in South Africa
11.5.4 Rest of Middle East and Africa
11.6 Latin America
11.6.1 Brazil
11.6.1.1 Increasing Proliferation of Consumer Data and Rising Demand for Data-Driven Enterprises for Quick and Real-Time Access to This Data to Boost the Demand for the Market in Brazil
11.6.2 Mexico
11.6.2.1 Government Initiatives in the Market Lead to Increasing Infrastructural Investments From Several Global Investors to Drive the Growth of the Overall Market in Mexico
11.6.3 Rest of Latin America

12 Competitive Landscape
12.1 Overview
12.2 Competitive Scenario
12.2.1 Product/Service/Solution Launches and Enhancements
12.2.2 Business Expansions
12.2.3 Acquisitions
12.2.4 Partnerships

13 Company Profiles
13.1 Introduction
13.2 Oracle
13.3 IBM
13.4 Hazelcast
13.5 Scale Out Software
13.6 Tibco Software
13.7 Red Hat
13.8 Software AG
13.9 Gigaspaces
13.10 Gridgain Systems
13.11 Alachisoft
13.12 Pivotal
13.13 Tmaxsoft
13.14 Hitachi

14 Appendix
14.1 Discussion Guide
14.2 Knowledge Store: Subscription Portal
14.3 Available Customizations
14.4 Related Reports
14.5 Author Details

List of Tables
Table 1 In Memory Data Grid Market Size, By Component, 2016–2023 (USD Million)
Table 2 Solution: Market Size By Region, 2016–2023 (USD Million)
Table 3 Professional Services Market Size, By Type, 2016–2023 (USD Million)
Table 4 Professional Services Market Size, By Region, 2016–2023 (USD Million)
Table 5 Consulting Market Size, By Region, 2016–2023 (USD Million)
Table 6 Support and Maintenance Market Size, By Region, 2016–2023 (USD Million)
Table 7 Education Market Size, By Region, 2016–2023 (USD Million)
Table 8 Business Application Market Size, By Type, 2016–2023 (USD Million)
Table 9 Transaction Processing: Market Size By Region, 2016–2023 (USD Million)
Table 10 Fraud and Risk Management: Market Size By Region, 2016–2023 (USD Million)
Table 11 Supply Chain Optimization: Market Size By Region, 2016–2023 (USD Million)
Table 12 Sales and Marketing Optimization: Market Size By Region, 2016–2023 (USD Million)
Table 13 In Memory Data Grid Market Size, By Industry Vertical, 2016–2023 (USD Million)
Table 14 Banking, Financial Services, and Insurance: Market Size By Region, 2016–2023 (USD Million)
Table 15 Media and Entertainment: Market Size By Region, 2016–2023 (USD Million)
Table 16 Consumer Goods and Retail: Market Size By Region, 2016–2023 (USD Million)
Table 17 Healthcare and Life Sciences: Market Size By Region, 2016–2023 (USD Million)
Table 18 Manufacturing: Market Size By Region, 2016–2023 (USD Million)
Table 19 Telecom and It: Market Size By Region, 2016–2023 (USD Million)
Table 20 Transportation and Logistics: Market Size By Region, 2016–2023 (USD Million)
Table 21 Others: Market Size By Region, 2016–2023 (USD Million)
Table 22 In Memory Data Grid Market Size, By Organization Size, 2016–2023 (USD Million)
Table 23 Large Enterprises: Market Size By Region, 2016–2023 (USD Million)
Table 24 Small and Medium-Sized Enterprises: Market Size By Region, 2016–2023 (USD Million)
Table 25 Market Size By Deployment Type, 2016–2023 (USD Million)
Table 26 On-Premises: Market Size By Region, 2016–2023 (USD Million)
Table 27 Cloud: Market Size By Region, 2016–2023 (USD Million)
Table 28 In Memory Data Grid Market Size, By Region, 2016–2023 (USD Million)
Table 29 North America: Market Size By Component, 2016–2023 (USD Million)
Table 30 North America: Market Size By Professional Service, 2016–2023 (USD Million)
Table 31 North America: Market Size By Business Application, 2016–2023 (USD Million)
Table 32 North America: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 33 North America: Market Size By Organization Size, 2016–2023 (USD Million)
Table 34 North America: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 35 North America: Market Size By Country, 2016–2023 (USD Million)
Table 36 Europe: In Memory Data Grid Market Size, By Component, 2016–2023 (USD Million)
Table 37 Europe: Market Size By Professional Service, 2016–2023 (USD Million)
Table 38 Europe: Market Size By Business Application, 2016–2023 (USD Million)
Table 39 Europe: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 40 Europe: Market Size By Organization Size, 2016–2023 (USD Million)
Table 41 Europe: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 42 Europe: Market Size By Country, 2016–2023 (USD Million)
Table 43 Asia Pacific: In Memory Data Grid Market Size, By Component, 2016–2023 (USD Million)
Table 44 Asia Pacific: Market Size By Professional Service, 2016–2023 (USD Million)
Table 45 Asia Pacific: Market Size By Business Application, 2016–2023 (USD Million)
Table 46 Asia Pacific: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 47 Asia Pacific: Market Size By Organization Size, 2016–2023 (USD Million)
Table 48 Asia Pacific: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 49 Asia Pacific: Market Size By Country, 2016–2023 (USD Million)
Table 50 Middle East and Africa: In Memory Data Grid Market Size, By Component, 2016–2023 (USD Million)
Table 51 Middle East and Africa: Market Size By Professional Service, 2016–2023 (USD Million)
Table 52 Middle East and Africa: Market Size By Business Application, 2016–2023 (USD Million)
Table 53 Middle East and Africa: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 54 Middle East and Africa: Market Size By Organization Size, 2016–2023 (USD Million)
Table 55 Middle East and Africa: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 56 Middle East and Africa: Market Size By Country, 2016–2023 (USD Million)
Table 57 Latin America: In Memory Data Grid Market Size, By Component, 2016–2023 (USD Million)
Table 58 Latin America: Market Size By Professional Service, 2016–2023 (USD Million)
Table 59 Latin America: Market Size By Business Application, 2016–2023 (USD Million)
Table 60 Latin America: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 61 Latin America: Market Size By Organization Size, 2016–2023 (USD Million)
Table 62 Latin America: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 63 Latin America: Market Size By Country, 2016–2023 (USD Million)
Table 64 Product/Service/Solution Launches and Enhancements, 2015–2018
Table 65 Business Expansions, 2016–2018
Table 66 Acquisitions, 2015–2018
Table 67 Partnerships, 2014–2018

List of Figures
Figure 1 Market Segmentation
Figure 2 In Memory Data Grid Market: Research Design
Figure 3 Market Bottom-Up Approach
Figure 4 Market Top-Down Approach
Figure 5 Large Enterprises Segment Holds the Highest Market Share in the In Memory Data Grid Market in 2018
Figure 6 Transaction Processing Segment Accounts for the Largest Market Size in 2018
Figure 7 North America Accounts for the Highest Share of the Market in 2018
Figure 8 Need for Distributed Data Storage Architecture for Faster Data Processing to Drive the Growth of the Market
Figure 9 Transaction Processing Segment and the US Account for the Highest Shares in the North America Market in 2018
Figure 10 Australia and New Zealand to Grow at the Highest Rate During the Forecast Period
Figure 11 In Memory Data Grid Market: Drivers, Restraints, Opportunities, and Challenges
Figure 12 Professional Services Segment to Grow at A Higher CAGR During the Forecast Period
Figure 13 Education Segment to Grow at the Highest CAGR During the Forecast Period
Figure 14 Fraud and Risk Management Segment to Grow at the Highest CAGR During the Forecast Period
Figure 15 Consumer Goods and Retail Industry Vertical to Grow at the Highest CAGR During the Forecast Period
Figure 16 Small and Medium-Sized Enterprises Segment to Grow at A Higher CAGR During the Forecast Period
Figure 17 Cloud Segment to Grow at A Higher CAGR During the Forecast Period
Figure 18 North America to Hold the Highest Market Share in 2018
Figure 19 Asia Pacific to Grow at the Highest CAGR During the Forecast Period
Figure 20 North America: Market Snapshot
Figure 21 Asia Pacific: Market Snapshot
Figure 22 Key Developments By the Leading Players in the In Memory Data Grid Market, 2014–2018
Figure 23 Geographic Revenue Mix of the Top Market Players
Figure 24 Oracle: Company Snapshot
Figure 25 IBM: Company Snapshot
Figure 26 Red Hat: Company Snapshot
Figure 27 Software AG: Company Snapshot
Figure 28 Pivotal: Company Snapshot
Figure 29 Hitachi: Company Snapshot

Note: Product cover images may vary from those shown
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  • Alachisoft
  • Gigaspaces
  • Gridgain Systems
  • Hazelcast
  • Hitachi
  • IBM
  • Oracle
  • Pivotal
  • Red Hat
  • Scale Out Software
  • Software AG
  • Tibco Software
  • Tmaxsoft
Note: Product cover images may vary from those shown
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