Meticulous Research® – a leading global market research company published a research report titled “Graph Analytics Market by Component, Deployment, Industry Size, Application (Customer Analytics, Recommendation Engine, Route Optimization, Fraud Detection), End User (BFSI, E-commerce, Healthcare, Manufacturing, Logistics) – Global Forecast to 2027”.

According to this latest publication from Meticulous Research®, the graph analytics market is expected to grow at a CAGR of 19.1% from 2019 to 2027 to reach $2.03 billion by 2027. This market is majorly driven by the growing demand to analyze low-latency queries, increasing demand for cloud-based services, and integrating AI, IoT, and Blockchain technologies across different end-use industries. In addition, emerging economies such as Asia-Pacific and Latin America are incorporating digital transformation at a considerable pace, which is offering significant growth opportunities for players operating in the graph analytics market. However, the lack of standardization and complex programming for use-cases obstructs the growth of this market.

Check complete table of contents with a list of table and figures: https://www.meticulousresearch.com/product/graph-analytics-market-5134

The graph analytics market study presents historical market data in terms of value and volume (2017 and 2018), estimated current data (2019), and forecasts for 2027. The market is segmented based on component (solution and services), deployment mode (on-premises and cloud), industry size (small & medium and large enterprises), application (customer analytics, risk & compliance management, recommendation engine, route optimization, fraud detection, and other), end user (BFSI, retail & e-commerce, telecom, healthcare, government, manufacturing, transportation & logistics, and other). The study also evaluates industry competitors and analyses the market at the country level.

Based on component, the graph analytics market is broadly segmented into solutions and services. In 2020, the solutions segment is expected to account for the largest share of the graph analytics market. The large share of this segment is mainly attributed to the growing demand to analyze low-latency queries, growing need to analyze data in real-time, and rapid use of virtualization for big data analytics. However, the graph analytics services segment is expected to grow with the fastest CAGR over the coming years. With gradual expansion of graph analytics across different domains, the demand for consulting, system integration, and support & maintenance is also expected to grow proportionally.

Based on deployment mode, the graph analytics market is segmented into on-premise and cloud-based. In 2020, the on-premise segment is projected to command the largest share of the market due to greater control over analytics infrastructure offered by on-premise solutions. On the other hand, the cloud-based segment is expected to grow at the fastest CAGR of during the forecast period. The growing sophistication in cloud deployments, increasing use of cloud network for different analytics, including prescriptive analytics, and superior flexibility offered by cloud deployments are the factors driving the growth of this segment.

Based on industry size, the graph analytics market is segmented into small & medium and large enterprises. In 2020, the large enterprises segment is expected to command the largest share of the graph analytics market due to its strong infrastructure and skilled IT personnel who maintain large volumes of graph database platforms. Besides, large enterprises focus on prescriptive analytics to retain their customers, boost their sales, and validate necessary steps to overcome market interruptions, such as COVID-19. However, the SMEs segment is expected to grow at the highest CAGR during the forecast period.

Based on application, the graph analytics market is segmented into customer analytics, risk & compliance management, recommendation engine, route optimization, fraud detection, and other applications. In 2020, the fraud detection segment is expected to command the largest share of the graph analytics market. The large share of this segment is mainly attributed to the rising number of fraudulent attacks, increasing use of electronic transactions across all verticals, and increasing sophistication of cyber-attacks. In addition, the growing adoption of technologies, such as AI and machine learning for fraud detection, could spur the demand for graph analytics solutions.

Geographically, the North American region is poised to command the largest share of the graph analytics market in 2020. This region focuses on adopting graph analytics solutions to enhance its IT infrastructure and leverage the benefits of new technologies, such as AI, blockchain, and IoT. This regional segment also boosts the presence of a majority of established graph analytics players and start-ups.
The key players operating in the graph analytics market are Neo4j Inc. (U.S.), TigerGraph (U.S.), TIBCO Software Inc. (U.S.), Oracle Corporation (U.S.), Microsoft Corporation (U.S.), Lynx Analytics (Singapore), Tom Sawyer Software (U.S.), IBM Corporation (U.S.), Cray Inc (U.S.), Datastax (U.S.), Objectivity (US), Kineviz (US), Franz (US), and Expero (US).

Key questions answered in the report
• Which are the high growth market segments in terms of component, deployment mode, industry size, application, end user, and countries?
• What is the historical market for graph analytics across the globe?
• What are the market forecasts and estimates from the period of 2019-2027?
• What are the major drivers, restraints, and opportunities in the graph analytics market?
• Who are the major players in the graph analytics market, and what share of the market do they hold?
• How is the competitive landscape?
• What are the recent developments in the graph analytics market?
• What are the different strategies adopted by the major players in the market?
• What are the geographic trends and high growth countries?
• Who are the local emerging players in the graph analytics market, and how do they compete with the other players?

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