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市场调查报告书
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1435937

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（2024-2029）

In Memory Data Grid - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 115 Pages | 商品交期: 2-3个工作天内

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简介目录

记忆体内资料网格市场规模预计到 2024 年为 38 亿美元，预计到 2029 年将达到 91.7 亿美元，预测期内（2024-2029 年）复合年增长率为 19.23%。

记忆体资料格 - 市场

随着对即时诈欺和风险管理能力的需求增加，记忆体内资料网格解决方案的采用预计会增加。

主要亮点

  • 记忆体内资料网格解决方案越来越多地被采用，因为它们可以提供高速资料处理和分析能力。随着云端运算的发展，企业越来越多地采用基于云端基础的记忆体内资料网格解决方案，这些解决方案提供了处理大量资料所需的弹性和扩充性，而无需本地基础设施。
  • 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征。因此，各行业的公司已开始投资这些解决方案，以加快决策速度并提高整体营运效率，从而推动市场需求。
  • 实施和管理记忆体内资料网格解决方案非常复杂，需要技术专业知识，这阻碍了技术资源有限的公司采用的市场成长。此外，高成本和资料安全等因素进一步限制了市场的成长。
  • 疫情导致人们迅速转向远端工作、电子商务和线上服务，从而导致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不断增加，从而增加了对记忆体内资料网格产品的需求。
  • 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，IT 预算的减少和企业面临的财务限制也减少了记忆体内资料网格解决方案的采用。

记忆体内资料网格市场趋势

BFSI 对即时资料处理不断增长的需求推动了市场成长

  • 日益数位化迫使金融公司开发精益、灵活和高效的方法来服务客户。金融机构处理敏感讯息，如果处理不当，可能会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寻求记忆体内资料网格解决方案来即时处理资料并改进关键业务应用程式。
  • BFSI 行业越来越多地采用云端运算也推动了记忆体内资料网格的成长，因为与本地传统解决方案相比，云端基础的记忆体资料网格解决方案提供了更大的弹性、扩充性和成本效率。需求。这些是 BFSI 组织的合适选择。
  • 此外，BFSI 产业对即时资料处理的需求不断增长，增加了对记忆体内资料网格、快速资料存取以及云端基础的部署在记忆体中储存和处理大量资料的适用性的需求。
  • 主要银行严重依赖 GridGain Systems Inc. （记忆体内资料网格的着名提供者之一）来帮助提供统一的全通路银行业务体验。透过 GridGain 解决方案，组织可以提高数位管道的速度和规模，开放先前孤立的资料并跨通路无缝共用，并利用即时串流分析、机器和深度学习。使用进程内 HTAP 主动交付端到端的银行业务体验。
  • 此外，由于 COVID-19感染疾病，银行内部和外部诈欺案件数量急剧增加。 COVID-19感染疾病带来的救济措施导致诈骗、虚假申请和其他诈骗增加。金融机构和政府机构建立的许多系统都要求对申请人的身份和申请进行适当的验证。例如，根据警察厅的数据，日本警方2022年记录了1,136起网路银行业务诈骗案件，与前一年相比大幅增加。

预计北美将占据主要份额

  • 由于各组织之间的监管合规性不断增强，以推动企业采用记忆体内资料网格记忆体内资料网格，预计北美在预测期内将在记忆体资料网格市场中占据更大份额，这表明该市场的潜在成长。
  • 该地区记忆体内资料网格的采用正在增加。这主要是由于对巨量资料的高速处理和分析的需求激增，再加上不同资料来源数量的增加而导致架构简化的需求。增强技术以优化整体拥有成本也是推动市场成长的因素。
  • 随着各种资料来源的增加，新业务洞察的成长将有助于美国市场的扩张。公司正在利用巨量资料来增强行销和客户体验，并识别可以直接提高业务成果的诈欺和风险。根据美国反保险诈欺联盟的统计，美国和加拿大保险公司 5% 到 10% 的保险申请成本是由于诈骗造成的。一些保险公司估计总金额高达申请成本的 20%。如果将北美地区所有保险产品总合，预计成本在800亿美元至900亿美元之间。
  • 医疗保健产业也正在成为领先的资料来源，采用云端来储存电子健康记录 (EHR)资料和其他企业应用程式。例如，根据美国资料分析公司 GNS Healthcare 的数据，美国美国产业每年大约产生 12 亿份临床护理文件。因此，最终用户行业资料的增加预计将创造即时处理，从而为市场创造机会。
  • 该地区知名企业的存在继续得到全球 2000 家组织的快速采用，其中包括许多世界领先的金融机构，如摩根大通、澳大利亚国民银行、劳埃德银行业务集团和瑞银产生收入。

记忆体内资料网格产业概述

记忆体内资料网格市场是分散的，由不同的供应商组成，例如 GridGain、Hazelcast、Software AG、Oracle Corporation 和 GigaSpaces Technologies Inc。供应商正在部署多种有机和无机成长策略，例如伙伴关係和协作、新产品发布以及併购，以增强其影响力并在市场中竞争。

2022 年 3 月 Hazelcast 宣布推出 InApps 技术，这是一种开放原始码、轻量级记忆体内流处理引擎，可实现智能家居传感器、店内电子商务系统和社交媒体平台等资料密集型应用程序的近实时处理。 。 、日誌分析、监控和诈欺侦测。该公司还发布了 Hazelcast IMDG 3.8 版本。它包括用于管理持久性和多资料部署的高级功能。

2022 年 3 月 Hazelcast 为其记忆体内资料网格软体新增了 SQL 串流资料功能和分层功能，以便您可以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，这使得存取、处理和分析资料的速度比从 SSD 或磁碟机顺序读取资料快得多。

其他福利

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

目录

第一章 简介

  • 研究假设和市场定义
  • 调查范围

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
    • 买方议价能力
    • 供应商的议价能力
    • 新进入者的威胁
    • 替代产品的威胁
    • 竞争公司之间的敌意强度
  • 评估新型冠状病毒感染疾病（COVID-19）对市场的影响

第五章市场动态

  • 市场驱动因素
    • 对达到前所未有的资料处理速度水准的需求日益增长
    • 巨量资料的成长
  • 市场挑战
    • 维护资料安全

第六章市场区隔

  • 按成分分类
    • 解决方案
    • 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 竞争形势

  • 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9章市场的未来

简介目录
Product Code: 71193

The In Memory Data Grid Market size is estimated at USD 3.80 billion in 2024, and is expected to reach USD 9.17 billion by 2029, growing at a CAGR of 19.23% during the forecast period (2024-2029).

In Memory Data Grid - Market

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