查看购物车
  • Traditional Chinese
  • English
  • Japanese
封面
市场调查报告书
商品编码
1644341

记忆体内资料网格：市场占有率分析、产业趋势与统计、成长预测（2025-2030）

In Memory Data Grid - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 115 Pages | 商品交期: 2-3个工作天内

价格

※ 本网页内容可能与最新版本有所差异。详细情况请与我们联繫。

简介目录

记忆体内资料网格市场规模预计在 2025 年为 45.3 亿美元，预计到 2030 年将达到 109.2 亿美元，预测期内（2025-2030 年）的复合年增长率为 19.23%。

记忆体资料网格-市场-IMG1

随着对即时诈欺和风险管理能力的需求不断增长，记忆体内资料网格解决方案的采用预计也会成长。

主要亮点

  • 记忆体内资料网格解决方案因其能够提供高速资料处理和分析能力而变得越来越流行。云端运算的发展导致云端基础的记忆体内资料网格解决方案的采用率不断提高，该解决方案提供了处理大量资料所需的灵活性和扩充性，而无需内部部署基础设施。
  • 此外，疫情凸显了即时资料处理和分析的重要性，这是记忆体内资料网格解决方案的关键特性。因此，各行各业的企业都开始投资这些解决方案，以便更快地做出决策并提高整体业务效率，从而推动市场需求。
  • 记忆体内资料网格解决方案的实现和管理很复杂，需要技术专长，这阻碍了技术资源有限的企业采用它们。此外，高成本和资料安全等因素进一步抑制了市场成长。
  • 疫情导致人们突然转向远端工作、电子商务和线上服务，从而对记忆体内资料网格解决方案的需求激增。随着越来越多的人远端工作，对可靠、高效的资料处理和分析解决方案的需求也随之增加，从而导致对记忆体内资料网格产品的需求增加。
  • 然而，供应链中断导致产品发布和交货延迟，影响了市场成长。此外，企业面临的 IT 预算减少和财务限制也导致记忆体内资料网格解决方案的采用率下降。

记忆体内资料网格市场趋势

BFSI 对即时资料处理的需求不断增长，推动市场成长

  • 数位化的兴起迫使金融机构开发精益、灵活、有效率的方法来服务客户。金融机构处理敏感讯息，如果处理不当，可能产生严重的财务和道德影响。因此，世界各地的金融机构都在转向记忆体内资料网格解决方案来即时处理资料并为其业务关键型应用程式提供支援。
  • 云端处理在 BFSI 行业中的日益普及也推动了对记忆体内资料网格的需求。云端基础的记忆体内资料网格解决方案比传统的内部部署解决方案更灵活、扩充性且更具成本效益，是 BFSI 组织的正确选择。
  • 此外，BFSI 行业对即时资料处理的需求日益增长，这推动了对记忆体内资料网格可在记忆体中储存和处理大量资料、快速资料存取以及适合云端基础的部署。
  • 领先的银行严重依赖 GridGain Systems Inc.（记忆体内资料网格的着名提供者之一）来提供整合的全通路银行体验。 GridGain 的解决方案使公司能够提高数位管道的速度和规模，解锁先前孤立的资料以便跨通路无缝共用，使用即时串流分析、机器学习和深度学习实现流程内 HTAP，并主动监控和增强端到端银行体验。
  • 此外，由于新冠疫情爆发，银行内部和外部诈骗案件激增。新冠疫情救助计画导致诈骗、虚假索赔和其他诈骗的增加。许多金融机构和政府机构实施的系统都要求对申请人的身份和索赔进行广泛的验证。例如，根据日本警察厅统计，2022年日本警方记录了1,136起网路银行诈骗案件，较前一年大幅增加。

预计北美将占很大份额

  • 预计预测期内北美将占据记忆体内资料网格市场的大部分份额。这是由于企业之间的监管合规性不断提高，推动了整个企业采用记忆体内资料网格，显示潜在的市场成长。
  • 该地区对记忆体内资料网格的采用日益广泛，主要是由于对巨量资料快速处理和分析的需求激增，以及随着各种资料来源的增加，简化架构的需求日益增长。优化整体拥有成本的技术改进也是推动市场成长的因素之一。
  • 在美国，新商业洞察力的成长加上各种资料来源的增加正在促进市场扩张。公司正在利用巨量资料来增强行销、客户体验，并透过识别诈欺和风险直接提高业务绩效。据美国反保险诈欺联盟称，诈骗占美国和加拿大保险公司索赔成本的5-10％。一些保险公司估计总合可能高达索赔成本的 20%。北美所有业务线的成本估计在 800 亿美元至 900 亿美元之间。
  • 随着医疗保健行业采用云端运算来储存电子健康记录(EHR)资料和其他企业应用程序，该行业也正在成为主要的资料来源。例如，根据美国资料分析公司GNS Healthcare估计，美国医疗保健产业每年产生12亿份临床照护文件。因此，预计终端用户行业资料的成长将推动即时处理，从而创造市场机会。
  • 知名参与者的存在，以及包括摩根大通、澳洲国民银行、劳埃德银行集团和瑞银等许多世界领先金融机构在内的全球 2000 强企业的迅速采用，为该地区的产生收入做出了贡献。

记忆体内资料网格产业概览

记忆体内资料网格市场由各种供应商分割，例如 GridGain、Hazelcast、Software AG、Oracle Corporation、GigaSpaces Technologies Inc.为了扩大市场占有率并保持竞争优势，供应商正在实施有机和无机成长策略，例如伙伴关係、协作、新产品推出和併购。

2022 年 3 月，Hazelcast 宣布推出 InApps 技术，开放原始码、轻量级、记忆体内流处理引擎，可近乎实时地处理资料密集型应用程序，例如智能家居传感器、店内电子商务系统、社交媒体平台、日誌分析、监控和诈欺检测。我们还发布了 Hazelcast IMDG 3.8 版本，具有管理持久性和多资料部署的高级功能。

2022 年 3 月，Hazelcast 在其记忆体内资料网格软体中添加了更多 SQL 流资料功能和分层功能，允许同时查询即时资讯和旧资讯。该公司基本上将大量资料储存在记忆体中，以便能够比从 SSD 或磁碟机顺序读取资料更快地存取、处理和分析资料。

其他福利：

  • Excel 格式的市场预测 (ME) 表
  • 3 个月的分析师支持

目录

第 1 章 简介

  • 研究假设和市场定义
  • 研究范围

第二章调查方法

第三章执行摘要

第四章 市场洞察

  • 市场概况
  • 产业吸引力－波特五力分析
    • 购买者/消费者的议价能力
    • 供应商的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争对手之间的竞争强度
  • COVID-19 市场影响评估

第五章 市场动态

  • 市场驱动因素
    • 需要前所未有的资料处理速度
    • 巨量资料的成长
  • 市场挑战
    • 维护资料安全

第六章 市场细分

  • 按组件
    • 解决方案
    • 按服务
  • 依部署类型
    • 本地
    • 云
  • 按最终用户产业
    • BFSI
    • 资讯科技/通讯
    • 零售
    • 卫生保健
    • 运输和物流
    • 其他最终用户产业
  • 按地区
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
    • 中东和非洲

第七章 竞争格局

  • 公司简介
    • Hazelcast Inc.
    • GridGain Systems Inc.
    • Oracle Corporation
    • IBM Corporation
    • Pivotal（VMware Inc.）
    • GigaSpaces Technologies Inc.
    • Software AG
    • ScaleOut Software
    • Alachisoft
    • TIBCO Software Inc.

第八章投资分析

第九章：市场的未来

简介目录
Product Code: 71193

The In Memory Data Grid Market size is estimated at USD 4.53 billion in 2025, and is expected to reach USD 10.92 billion by 2030, at a CAGR of 19.23% during the forecast period (2025-2030).

In Memory Data Grid - Market - IMG1

As the need for real-time fraud and risk management capabilities continues to grow, the adoption of in-memory data grid solutions is expected to increase.

Key Highlights

  • In-memory data grid solutions have been increasingly gaining adoption due to their ability to provide high-speed data processing and analysis capabilities. With the growth of cloud computing, businesses are increasingly adopting cloud-based in-memory data grid solutions that provide the flexibility and scalability needed to handle large amounts of data without the need for on-premises infrastructure.
  • Furthermore, the pandemic emphasized the significance of real-time data processing and analysis, which is a key feature of in-memory data grid solutions. As a result, businesses in various industries began to invest in these solutions in order to enable faster decision-making and improve overall operational efficiency driving the demand in the market.
  • As the implementation and managing in-memory data grid solutions are complex and require technical expertise, their adoption from businesses with limited technical resources is hampering the market growth. Also, the factors such as higher cost and data security are further restraining the market growth.
  • The pandemic led to a sudden shift towards remote working, e-commerce, and online services, which has created a surge in demand for in-memory data grid solutions. With more people working remotely, the need for reliable and efficient data processing and analytics solutions has increased, leading to a rise in demand for in-memory data grid products.
  • However, the supply chain disruptions led to delays in product launches and delivery, which affected the growth of the market. Also, the reduced IT budgets and financial constraints faced by businesses resulted in a decrease in the adoption of in-memory data grid solutions.

In Memory Data Grid Market Trends

Growing Need for Real Time Data Processing in BFSI Driving the Market Growth

  • Growing digitalization is compelling financial companies to build a lean, flexible, and efficient approach to cater to their customers. Financial institutions deal with critical information, which, if not properly processed, can have severe financial and ethical implications. Thus, financial organizations worldwide seek in-memory data grid solutions to process data in real-time and improve their business-critical applications.
  • The growing adoption of cloud computing in the BFSI industry is also driving the demand for in-memory data grids, as cloud-based in-memory data grids solutions provide greater flexibility, scalability, and cost-effectiveness compared to on-premises traditional solutions making them a suitable option for BFSI organizations.
  • Furthermore, the growing need for real-time data processing in the BFSI industry is increasing the demand for in-memory data grids to store and process large volumes of data in memory, high-speed data access, and suitability for cloud-based deployments.
  • Leading banks significantly depend on GridGain Systems Inc., one of the prominent providers of In-memory data grids, to help them offer an integrated omnichannel banking experience. By using the GridGain solution, organizations have added speed and scale to digital channels, opened up previously siloed data for seamless sharing across channels, and implemented in-process HTAP using real-time streaming analytics, machine, and deep learning to monitor and enhance the end-to-end banking experience proactively.
  • Moreover, banks witnessed a sharp rise in internal and external fraud cases from the COVID-19 outbreak. The COVID-19 outbreak rescue package increased fraud, false claims, and other scams. Many of the systems that financial institutions and government agencies in place needed to verify the identity and claims of applicants adequately. For instance, according to National Police Agency Japan, the police in Japan recorded 1,136 online banking fraud cases in 2022, which constituted a substantial increase compared to the previous year.

North America is Expected to Hold Major Share

  • North America is expected to account for a larger share of the In-memory data grid market during the forecast period due to increasing regulatory compliances among organizations to boost in-memory data grid adoption across enterprises, indicating potential market growth.
  • The adoption of an in-memory data grid is rising in the region, primarily attributed to the burgeoning demand for faster processing and analytics on big data coupled with the need for simplifying architecture as the number of various data sources increases. Technology enhancements that optimize the total ownership cost are another factor driving the market growth.
  • The growth of new business insights contributes to expanding the market in the United States as various data sources increase. Multiple companies are leveraging big data to enhance marketing and customer experience and identify fraud and risk that can directly strengthen business performance. According to the US-based Coalition Against Insurance Fraud, fraud accounts for 5-10% of claims costs for American and Canadian insurers. Some insurers expect the total to be as high as 20% of the claims costs. Across all insurance lines in the North American region, the estimated cost is between USD 80 billion and USD 90 billion.
  • The healthcare industry, which embraces the cloud for its Electronic health record (EHR) data and other enterprise applications, is also becoming a great data source. For instance, according to GNS Healthcare, a US-based Data Analytics Company, the United States healthcare industry generates an estimated 1.2 billion clinical care documents annually. Hence, growth in data across end-user industries is anticipated to create real-time processing, thereby creating opportunities for the market.
  • The presence of a prominent player, which continues to see rapid adoption among Global 2000 organizations, including many of the world's leading financial institutions, such as JPMorgan Chase, National Australia Bank, Lloyds Banking Group, UBS, and many more, is contributing to the revenue generation in the region.

In Memory Data Grid Industry Overview

The In-Memory Data Grid market is fragmented consisting of various vendors such as GridGain, Hazelcast, Software AG, Oracle Corporation, GigaSpaces Technologies Inc., and others. Vendors are deploying several organic and inorganic growth strategies, such as partnerships and collaborations, new product launches, and mergers and acquisitions, to strengthen their presence and compete in the market.

In March 2022, Hazelcast launched an open-source lightweight in-memory stream processing engine InApps technology, to enable processing in near real-time for data-intensive applications such as smart home sensors, in-store e-commerce systems, social media platforms, log analysis, monitoring, and fraud detection. The company also released version 3.8 of Hazelcast IMDG, which includes advanced capabilities for managing persistence and multi-data center deployments.

In March 2022, Hazelcast added more SQL streaming data capabilities and tiering to its in-memory data grid software so that real-time and older information can be queried simultaneously. The company basically stores a load of data in memory so it can be accessed, processed, and analyzed much faster than by sequentially reading it from SSDs or disk drives.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Buyers/Consumers
    • 4.2.2 Bargaining Power of Suppliers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Assessment of the Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Need for Attaining Unprecedented Levels of Speed at Data Processing
    • 5.1.2 Growth of Big Data
  • 5.2 Market Challenges
    • 5.2.1 Maintaining Data Security

6 MARKET SEGMENTATION

  • 6.1 By Component
    • 6.1.1 Solution
    • 6.1.2 Services
  • 6.2 By Deployment Type
    • 6.2.1 On-premise
    • 6.2.2 Cloud
  • 6.3 By End-user Industry
    • 6.3.1 BFSI
    • 6.3.2 IT and Telecommunication
    • 6.3.3 Retail
    • 6.3.4 Healthcare
    • 6.3.5 Transportation and Logistics
    • 6.3.6 Other End-User Industries
  • 6.4 By Geography
    • 6.4.1 North America
    • 6.4.2 Europe
    • 6.4.3 Asia-Pacific
    • 6.4.4 Latin America
    • 6.4.5 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Hazelcast Inc.
    • 7.1.2 GridGain Systems Inc.
    • 7.1.3 Oracle Corporation
    • 7.1.4 IBM Corporation
    • 7.1.5 Pivotal (VMware Inc.)
    • 7.1.6 GigaSpaces Technologies Inc.
    • 7.1.7 Software AG
    • 7.1.8 ScaleOut Software
    • 7.1.9 Alachisoft
    • 7.1.10 TIBCO Software Inc.

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET