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市場調查報告書
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1432893

複雜事件處理：市場佔有率分析、產業趨勢與統計、成長預測（2024-2029）

Complex Event Processing - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

複雜事件處理市場規模預計到2024年為52.7億美元，預計到2029年將達到153.1億美元，在預測期內（2024-2029年）複合年成長率預計為23.76%。

複雜事件處理市場

隨著感測器和連接設備的普及，儲存的資料量呈指數級成長。傳統的 DBMS 技術面臨即時分析這些資料的挑戰。複雜事件處理（CEP）可以解決這個問題，因為它對累積的查詢而不是累積的資料進行操作。

主要亮點

  • 巨量資料) 的興起正在推動對 CEP 解決方案的需求。巨量資料和物聯網產生大量資料，很難使用傳統方法進行分析。因此，分析這些資料並識別模式和趨勢正在推動複雜事件處理市場的採用。
  • 近年來，隨著網路革命，對即時資料分析的需求增加了一倍。公司正在大力投資工業自動化並不斷進步機器學習。此外，各種行業和巨量資料正在使網路變得更加複雜，最終推動複雜事件處理市場的發展。
  • 隨著即時資料分析的需求，儲存的資料量經常達到高水準。因此，對高效 CEP 系統進行有效即時資料處理的需求日益成長。根據 AI、Data & Analytics Network 於 2022 年 11 月發布的一項全球調查，高階分析投資的首要領域是複雜事件處理，52% 的公司已經對此進行了投資。
  • 然而，為各種應用程式實施複雜的事件處理解決方案的成本很高，阻礙了中小型企業的採用。此外，資料流的複雜性使得 CEP 難以識別模式。
  • 隨著企業和組織轉向數位管道與客戶和員工互動，新冠病毒大流行導致資料生成激增，以及獲取資料洞察和即時採取行動的複雜性，對事件處理解決方案的需求增加。此外，疫情也催生了人工智慧 (AI) 和機器學習 (ML) 等新技術的使用，以提高 CEP 解決方案的效率。

複雜事件處理 (CEP) 市場趨勢

BFSI 最終用戶群顯著成長

  • BFSI 行業越來越依賴即時資料分析、風險管理、詐欺檢測、合規性和以客戶為中心的方法，這極大地推動了全球對複雜事件處理的需求。 CEP 是金融機構的重要技術，因為它能夠即時處理和分析大量資料、發現模式並採取行動。
  • 信用卡公司擴大使用複雜的事件處理解決方案和巨量資料分析來有效管理詐欺。當詐欺活動模式出現時，該公司會處理動態資料流，從而在造成重大損失之前快速凍結信用卡。底層系統預計將關聯傳入的事務、追蹤事件資料流和觸發流程。
  • 銀行業和其他金融組織擴大使用複雜的事件處理來檢測詐欺，這可能會在未來幾年對該行業的發展做出重大貢獻。因此，複雜事件處理業務的佔有率和規模可望擴大。
  • 銀行和公司正在投資區塊鏈技術，創建 CEP 系統的使用。 CEP 系統有助於整合各種營業單位、客戶、系統和技術之間的數位交易的生命週期。 CEP 需要配置事件處理程序來偵聽區塊鏈或連接端點中的變更、關聯並呼叫適當的 CEP 規則來衍生操作或警報。
  • 該統計數據顯示了 2022 年按行業分類的 IT 支出在全球企業收益中所佔的佔有率。 Flexera Software 表示，軟體和技術託管/雲端和金融服務公司在 IT 上的支出遠高於其他產業。金融服務業將約 10% 的收入投資於 IT。

北美預計將佔據主要市場佔有率

  • 北美各最終用戶產業對物聯網 (IoT) 和巨量資料技術的採用顯著增加。許多組織從多個來源產生和收集大量資料，以深入了解客戶業務效率、行為和詐欺偵測。在此類應用中，CEP 擴大用於分析這些即時資料。
  • 該地區是複雜事件處理技術的早期採用者。該地區的幾家領先供應商已經開發了複雜的事件處理解決方案，並在各種應用中展示了它們的優勢。這種早期採用創造了有利的市場環境，促進了進一步的成長和採用。
  • 例如，2022 年 7 月，IBM 宣布其業務自動化產品組合包括 IBM Decision Manager Open Edition，這是其決策管理功能的最新補充，由企業級營運決策管理器和低程式碼的下一代自動化決策服務組成。已擴大。 IBM Decision Manager Open Edition 提供基於 Kogito 的雲端原生架構、符合 DMN1.4 的執行時間以及複雜的事件處理。
  • 美國在各行業的技術發展上也一直走在前面。這種環境正在推動複雜事件處理技術的發展和採用。

複雜事件處理 (CEP) 產業概述

複雜事件處理市場處於半固體，IBM、 Oracle、SAP、Software AG 和 Tibco Software 等主要企業佔據了重要的市場佔有率。為了在競爭中生存，在這個市場上營運的參與者正在投資產品推出、併購和市場競爭。

2022 年 7 月，IBM 將擴展其業務自動化產品組合，包括 IBM Decision Manager Open Edition，這是其決策管理功能的最新補充，由企業級營運決策管理器和低程式碼的下一代自動化決策服務組成。擴​​大了。 IBM Decision Manager Open Edition 提供基於 Kogito 的雲端架構、符合 DMN1.4 的執行時間以及複雜的事件處理。

2022 年 2 月，複雜事件流處理軟體領域的領先公司之一 thatDot, Inc. 發布了 Quine。這種獨特的方法將圖形資料和串流技術整合到一個現代的、開發人員友好的開放原始碼軟體中。

其他福利

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 技術簡介
  • 產業價值鏈分析
  • 產業吸引力－波特五力分析
    • 買家/消費者的議價能力
    • 供應商的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間敵對關係的強度
  • COVID-19 市場影響評估

第5章市場動態

  • 市場促進因素
    • 機器學習和資料分析領域的發展
    • 即時分析的需求不斷成長
  • 市場限制因素
    • 結果缺乏一致性

第6章市場區隔

  • 按類型
    • 軟體
    • 服務
  • 按公司類型
    • 中小企業
    • 主要企業
  • 按行業分類
    • BFSI
    • 管理流動性
    • 政府/國防
    • 零售
    • 衛生保健
    • 通訊/IT產業
    • 媒體娛樂
    • 製造業
    • 其他最終用戶產業
  • 按地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東/非洲

第7章 競爭形勢

  • 公司簡介
    • IBM Corporation
    • SAP SE
    • Oracle Corporation
    • Tibco Software Inc.
    • Software AG
    • SAS Institute Inc.
    • Informatica Corporation
    • Nastel Technologies Inc.
    • Espertech Inc.
    • Cisco Systems Inc.
    • Red Lambda Inc.

第8章投資分析

第9章 市場機會及未來趨勢

簡介目錄
Product Code: 55203

The Complex Event Processing Market size is estimated at USD 5.27 billion in 2024, and is expected to reach USD 15.31 billion by 2029, growing at a CAGR of 23.76% during the forecast period (2024-2029).

Complex Event Processing - Market

With the growing use of sensors and connecting devices, the amount of data getting stored is increasing exponentially. In the traditional DBMS method, the problem of analyzing this data on a real-time basis is a challenge. Complex Event Processing (CEP) addresses this problem in response, as it works on the stored query rather than stored data.

Key Highlights

  • The rise of big data and the Internet of Things (IoT) drives the demand for CEP solutions. Big data and IoT generate massive amounts of data that are difficult to analyze using traditional methods. Thus, analyzing this data and identifying patterns and trends have propelled the adoption of the Complex Event Processing Market.
  • With the internet revolution, the need for real-time data analytics has multiplied over the past few years. Companies are investing highly in industrial automation, raising the developments in machine learning. Additionally, varied industries, along with Big Data, are making the web more complicated, ultimately driving the complex event processing market.
  • Along with the need for real-time data analytics, the amount of data getting stored is reaching high regularly. Hence, the demand for efficient CEP systems for effective real-time data processing is growing. According to a global survey released in November 2022 by the AI, Data & Analytics Network, the top area of investment in advanced analytics is complex event processing, as 52% of companies are already investing in it.
  • However, the high implementation cost of complex event processing solutions for different applications is high, preventing small and medium-sized businesses from adopting them. Also, the complexities involved in the data streams make it challenging for the CEP to recognize patterns.
  • The COVID pandemic resulted in a surge in data generation, as businesses and organizations turned to digital channels to interact with customers and employees, which led increased need for complex event processing solutions to get insights into data and take action in real-time. Further, the pandemic led to the use of new technologies, such as artificial intelligence (AI) and machine learning (ML) to improve the efficiency of CEP solutions.

Complex Event Processing (CEP) Market Trends

BFSI End-user Segment to Grow Significantly

  • The BFSI sector's growing reliance on real-time data analysis, risk management, fraud detection, compliance, and customer-centric approaches have significantly fueled global demand for complex event processing. CEP is an essential technology for financial institutions because of its capacity to process and analyze enormous amounts of data in real time, find patterns, and initiate actions.
  • Credit card companies increasingly use complex event processing solutions with Big Data analytics to manage fraudulent activities efficiently. When a pattern of fraud incidence emerges, the company can block the credit card quickly before it can experience significant losses, as it deals with the moving flow of data. The underlying system is expected to correlate the incoming transactions, track the event data stream, and trigger a process.
  • Factors for the increased use of complex event processing for fraud detection in the banking sector and other financial organizations will significantly contribute to this industry segment's development in the coming years. This, in turn, will increase the share and size of the complex event-processing business.
  • Banks and trading companies are investing in blockchain technology, which is giving rise to using CEP systems. CEP systems help integrate the digital transaction lifecycle among various business entities, customers, systems, and technologies. With CEP, event handlers must be configured to listen for changes in the blockchain or the connected endpoints and then correlate and invoke appropriate CEP rules to derive an action or alert.
  • This statistic shows IT spending as a share of companies' revenue by industry worldwide in 2022. According to Flexera Software, software and tech hosting/cloud, and financial services companies spend much more on IT than other industries. The financial services industry invests around 10% of its revenue in IT.

North America Expected to Hold Major Market Share

  • The adoption of the Internet of Things (IoT) and big data technology in various end-user verticals in North America is increasing significantly. Many organizations are generating and collecting large amounts of data from multiple sources to gain insights into customer operational efficiency, behavior, and fraud detection. In such applications, CEP is increasingly used to analyze this real-time data.
  • The region has witnessed the early adoption of complex event-processing technologies. Several prominent regional vendors have developed complex event-processing solutions and demonstrated their benefits in various applications. This early adoption has created a favorable market environment, driving further growth and adoption.
  • For instance, in July 2022, IBM expanded its business automation portfolio, including IBM Decision Manager Open Edition, the latest addition to its decision management capabilities consisting of the enterprise-grade Operational Decision Manager and low-code, next-generation Automation Decision Services. It offers Kogito-based cloud-native architecture, DMN1.4-compliant runtime, and complex event processing.
  • In addition, the United States has been at the forefront of technological advancements in various industries for technology development. This environment fosters the growth and adoption of complex event-processing technologies.

Complex Event Processing (CEP) Industry Overview

The complex event processing market is semi-consolidated, with significant players such as IBM, Oracle, SAP, Software AG, and Tibco Software collectively accounting for a substantial market share. The players operating in the market have been investing in product launches, mergers and acquisitions, and collaboration activities to stay ahead of the competition.

In July 2022, IBM expanded its business automation portfolio, including IBM Decision Manager Open Edition, the latest addition to its decision management capabilities consisting of the enterprise-grade Operational Decision Manager and low-code, next-generation Automation Decision Services. It offers Kogito-based cloud-native architecture, DMN1.4-compliant runtime, and complex event processing.

In February 2022, thatDot, Inc., one of the leading companies in complex event stream processing software, released Quine. This unique approach combines graph data and streaming technologies into a modern, developer-friendly, open-source software package.

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 Technology Snapshot
  • 4.3 Industry Value Chain Analysis
  • 4.4 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.4.1 Bargaining Power of Buyers/Consumers
    • 4.4.2 Bargaining Power of Suppliers
    • 4.4.3 Threat of New Entrants
    • 4.4.4 Threat of Substitute Products
    • 4.4.5 Intensity of Competitive Rivalry
  • 4.5 Assessment of the Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Development in the Field of Machine Learning and Data Analytics
    • 5.1.2 Growing Need for Real-time Analytics
  • 5.2 Market Restraints
    • 5.2.1 Lack of Consistency in Results

6 MARKET SEGMENTATION

  • 6.1 By Type
    • 6.1.1 Software
    • 6.1.2 Services
  • 6.2 By Enterprise Type
    • 6.2.1 Small and Medium Enterprise
    • 6.2.2 Large Enterprise
  • 6.3 By End-user Vertical
    • 6.3.1 BFSI
    • 6.3.2 Managed Mobility
    • 6.3.3 Government and Defense
    • 6.3.4 Retail
    • 6.3.5 Healthcare
    • 6.3.6 Telecom and IT Industry
    • 6.3.7 Media and Entertainment
    • 6.3.8 Manufacturing
    • 6.3.9 Other End-user Verticals
  • 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 & Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 IBM Corporation
    • 7.1.2 SAP SE
    • 7.1.3 Oracle Corporation
    • 7.1.4 Tibco Software Inc.
    • 7.1.5 Software AG
    • 7.1.6 SAS Institute Inc.
    • 7.1.7 Informatica Corporation
    • 7.1.8 Nastel Technologies Inc.
    • 7.1.9 Espertech Inc.
    • 7.1.10 Cisco Systems Inc.
    • 7.1.11 Red Lambda Inc.

8 INVESTMENT ANALYSIS

9 MARKET OPPORTUNITIES AND FUTURE TRENDS