Complex Event Processing Addresses the Problem of Analyzing Real Time Data : Complex Event Processing Market – Growth, Trends, and Forecast, 2019 – 2024 – ResearchAndMarkets.com

DUBLIN–(BUSINESS WIRE)–The “Complex Event Processing Market – Growth, Trends, and Forecast (2019 – 2024)” report has been added to ResearchAndMarkets.com’s offering.

Market Overview

The complex event processing market is expected to register a CAGR of 28.74% over the forecast period 2019-2024. With the growing use of sensors and connecting devices, the amount of data getting stored is increasing tremendously. By traditional DBMS method, the problem of analyzing this data at a real-time basis is the challenge. In response, Complex Event Processing (CEP) addresses this problem as it works on the stored query rather than stored data.

  • The advantages of CEP approach are distinct, given that these queries are applied on a potentially infinite stream of data. Furthermore, inputs are processed immediately. Once the system processes all events for a matching sequence, results are shown directly. This aspect effectively leads to CEP’s real-time analytics capability.
  • With the revolution of the internet, the need for real-time data analytics growing rapidly from the past few years. Companies are making high investments for industrial automation, rising the developments in machine learning. Also, with varied industries, along with big data, is making the web more complicated, ultimately driving the complex event processor market.
  • Along with the need for real-time data analytics, the amount of data getting stored daily is reaching a new high regularly. Hence, the demand for efficient CEP systems to effective real-time data processing is growing.

Scope of the Report

The increasing complexity of industrial automation software solutions and the need for real-time analytics is demanding CEP solutions across the industries. The scope of the study for complex event processing market has considered both services as well as software solutions for different types of enterprises across the end-user verticles globally.

Key Market Trends

BFSI End-user Segment to Grow Significantly

  • With globally increasing IT spending towards enterprise software and communication services, which is estimated to be close to 50% of the global IT spending in 2018, CEP solutions gained a lot of attention, especially from BFSI sector for real-time analysis and gathering business intelligence for better decision making.
  • Credit card companies use CEP with Big Data Analytics to manage fraud better. When a pattern of fraud incidence emerges, the company can block the credit card quickly before the company can experience significant losses as it deals with the moving flow of data. The underlying system will correlate the incoming transactions, track the stream of event data, and trigger a process.
  • Banks and trading companies are highly investing in blockchain technology which is giving rise to the use of CEP systems. CEP systems help in integrating the lifecycle of digital transactions among various business entities, customers, systems, and technologies. With CEP, event handlers need to be configured to listen for changes in the blockchain, or the connected endpoints and then correlate and invoke appropriate CEP rules to either derive an action or alert.
  • BFSI sector contributes 40% of the TCS revenue, the rising adoption of technologies like blockchain and Big Data Analytics in the sector is giving rise to the application of CEP systems to formulate the decision making at a real-time basis.

Asia-Pacific to Witness Significant Growth

  • Asia-Pacific is one of the fastest developing regions in blockchain technology contributed to over 40% development in the world. The digitalization initiatives by the developing countries like India is driving the digital payments and banks are deploying the blockchain technology; hence, fuels the demand for CEP solution for its efficient integration.
  • Growth in the Asia-Pacific is mainly driven by government initiatives and large multi-million dollar technology deals in the banking vertical. Some of the others factors such as growing demand for data storage in small to medium enterprises (SMEs) and increasing proliferation of smartphones, laptops, and tablets in the Asia-Pacific region have augmented the demand machine learning applications in the region.
  • Retail and consumer goods companies in the region see the applicability of machine learning (ML) to drive improvements in customer service and operational efficiency. For instance, the Azure cloud is helping retail and consumer brands to improve the shopping experience by ensuring that shelves are stocked and the products are always available when, where and how the consumer wants to shop.


Key Topics Covered:


1.1 Study Deliverables

1.2 Study Assumptions

1.3 Scope of the Study




4.1 Market Overview

4.2 Technology Snapshot

4.3 Market Drivers

4.3.1 Development in the field of Machine Learning and Data Analytics

4.4 Market Restraints

4.4.1 Lack of Consistency in Results

4.5 Industry Value Chain Analysis

4.6 Industry Attractiveness – Porter’s Five Force Analysis

4.6.1 Threat of New Entrants

4.6.2 Bargaining Power of Buyers/Consumers

4.6.3 Bargaining Power of Suppliers

4.6.4 Threat of Substitute Products

4.6.5 Intensity of Competitive Rivalry


5.1 By Type

5.1.1 Software

5.1.2 Services

5.2 By Enterprise Type

5.2.1 Small and Medium Enterprise

5.2.2 Large Enterprise

5.3 By End-user Vertical

5.3.1 BFSI

5.3.2 Managed Mobility

5.3.3 Government and Defense

5.3.4 Retail

5.3.5 Healthcare

5.3.6 Telecom and IT Industry

5.3.7 Media and Entertainment

5.3.8 Manufacturing

5.3.9 Other End-user Verticals

5.4 Geography

5.4.1 North America

5.4.2 Europe

5.4.3 Asia-Pacific

5.4.4 Latin America

5.4.5 Middle East & Africa


6.1 Company Profiles

6.1.1 IBM Corporation

6.1.2 SAP SE

6.1.3 Oracle Corporation

6.1.4 Tibco Software Inc.

6.1.5 SAS Institute, Inc.

6.1.6 Informatica Corporation

6.1.7 Nastel Technologies, Inc.

6.1.8 Red Hat, Inc.

6.1.9 Software AG

6.1.10 Espertech, Inc.

6.1.11 Cisco Systems, Inc.

6.1.12 Red Lambda Inc.



For more information about this report visit https://www.researchandmarkets.com/r/pipjr2



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Related Topics: Data Analytics


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