The analysis of MRFR reveals that the Global Graph Analytics Market is slated to register a CAGR of 31.6% during the review period and reach a value of USD 2,885.2 Million in 2027.
The that need for real-time analyses of data and the convergence of the Internet of Things ( IoT), artificial intelligence, and block chain technologies are major factors that drive market growth. An additional factor driving the global graph analytics market is the growing demand for the analysis of low-latency queries. In addition, the lack of technical skills regarding graph analytics is expected to be a challenge to this market's growth. The rising need to identify complex patterns and the rapid use of Big Data Analytics virtualisation are the opportunities for the graph analysis market.
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The Global Graph Analytics Market has been segmented based on Deployment Type, Application, Organization Size, Vertical, Component, and Region/Country.
The global market in graph analytics was divided into solution and service by Component. The service segment was further divided into consulting, system integration, and maintenance and support.
The global graph analytics market was split into cloud and on-premise by Deployment Type. Most vendors in the graph analytics market offer cloud-based maintenance solutions to make maximum profits and effectively automate the process of maintenance of the equipment. It is expected that the adoption of cloud-based graph analytics solutions will increase due to benefits such as easy data maintenance, cost-effectiveness, scalability and effective management of these solutions.
The global graph analytics market was divided into small and medium-sized enterprises ( SMEs) and large enterprise segments, based on Organization Size.
The global graph analytics market, based on Application, was divided into risk and compliance management, customer analytics, route optimization, recommendation engines, fraud detection and others. The segment of route optimisation is expected to be the fastest growing segment on the market due to the increasing need to find the fastest and safest route in verticals, such as supply chain and logistics, transport, retail and eCommerce.
Based on Vertical, the global graph analytics market has been segmented into transportation & logistics, banking, financial services & insurance, healthcare & life sciences, government, telecom, retail and e-commerce, manufacturing,and others.
It is estimated that the Global Graph Analytics Market will record a CAGR of 31.6 per cent over the forecast period. Europe, Asia-Pacific, Middle East & Africa , North America, and Latin America performed the regional study of the global graph analytics sector.
North America has the largest market share as the key players in this region have been world leaders in technology advancement. Due to the high implementation of digital transformation, the US leads the market in North America; and the use of modern technologies such as big data and analytics, and the country's high adoption of cloud-based technologies.
Due to the high need for real-time data analysis between companies across verticals, Europe is expected to be the second-largest market during the review period. During the forecast period Asia-Pacific is expected to be the fastest-growing market on the global graph analytics market. The increasing demand for analysis of low-latency queries is the key driver for market growth in the Asia-Pacific region.
The Key Players in the Global Graph Analytics Market are Linkurious (France), Objectivity (UK), Neo4j (US), Graphistry (US), Dataiku (US), TIBCO Software (US), Teradata (US), Microsoft Corporation (US), Lynx Analytics (Singapore), IBM Corporation (US), AWS (US), Cray, Inc. (US), TigerGraph (US), DataStax (US), and Oracle Corporation (US).
The other players in the global graph analytics market include Kineviz (US), Franz (US), Tom Sawyer Software (US), and Expero (UK).
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Table of Contents
1 Executive Summary
2 Scope of The Report
2.1 Market Definition
2.2 Scope of The Study
2.2.1 Research Objectives
2.2.2 Assumptions & Limitations
2.3 Markets Structure
3 Market Research Methodology
3.1 Research Process
3.2 Secondary Research
3.3 Primary Research
3.4 Forecast Model
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