Global Graph Analytics Market: Analysis By Component (Solutions & Services), By Deployment (On Premise & Cloud), By Enterprise Size (Large Enterprises and Small and Medium Enterprises (SMEs)), By Application (Fraud Detection, Customer Analytics, Recommend

Global Graph Analytics Market: Analysis By Component (Solutions & Services), By Deployment (On Premise & Cloud), By Enterprise Size (Large Enterprises and Small and Medium Enterprises (SMEs)), By Application (Fraud Detection, Customer Analytics, Recommendation Engines, Risk & Compliance Management, Route Optimization & Others), By Industry Vertical (Banking, Financial Services and Insurance (BFSI), IT & Telecom, Manufacturing, Healthcare, Government, Retail & E-commerce, Education, Transportation & Others), By Region, Size and Trends with Impact of COVID-19 and Forecast up to 2028

The global graph analytics market in 2022 was valued at US$1.14 billion. The market value is anticipated to grow to US$6.90 billion by 2028. Graph analytics is a tool that analyses the direction and strength of relationships between objects in a graph. Graph analytics is the process of analyzing data represented in the form of a graph, which consists of nodes and edges that connect them. This type of analysis allows you to explore and uncover patterns and relationships within the data that may not be immediately apparent through other means. One of the key advantages of graph analytics is its ability to model complex systems and relationships. Traditional data analysis methods often rely on simple statistical techniques that assume linear relationships between variables. Graph analytics, on the other hand, can represent complex relationships between entities, such as social networks, supply chains, and biological systems, in a more natural and intuitive way.

The market value is expected to grow at a CAGR of 34.80% during the forecast period of 2023-2028. The growing demand for real-time analysis and identification of complex patterns, as well as the growing use of big data virtualization, are creating new growth opportunities for graph analytics vendors. Improved performance, scalability, reliability, better problem solving, and real-time application are some of the key benefits of implementing graph analytics solutions.

Market Segmentation Analysis:

By Component: The report provides the bifurcation of the market into two segments based on the component: Solutions and Services. In 2022, in terms of value, solutions segment held the major share in the market. The growing demand for analyzing low-latency queries, the increasing need to analyze data in real-time, and the rapid adoption of virtualization for big data analytics are driving the growth of this segment. Because of the benefits provided by these solutions, several providers are considering investing in R&D to make it better and more affordable for small and medium-sized businesses.

By Deployment: The report further provides the segmentation based on the deployment: On Premise and Cloud. During the forecast period, the cloud-based segment is expected to grow at the fastest CAGR. Cloud computing and storage systems are becoming increasingly popular among small and medium-sized businesses. Several organisations are gradually transitioning to cloud infrastructure, and this trend is expected to accelerate in the coming years. The advantages of cloud infrastructure, such as ease of adoption, reduced reliance on in-house infrastructure, scalability, and simple installation of security solutions, contribute to the segment's rapid growth.

By Enterprise Size: The graph analytics market is further bifurcated based on the enterprise size: Large Enterprises and Small and Medium Enterprises (SMEs). Large Enterprises dominated the market in 2022. Large-scale enterprises often have complex data governance requirements, and they need tools that can handle sensitive data securely. Graph analytics tools can be configured to meet these requirements, providing a high level of security and compliance. Large enterprises have strong infrastructure, coupled with skilled IT personnel, to maintain large volumes of graph database platform, which is driving the segment’s growth.

By Application: The report provides the bifurcation of the market into into six segments based on the application: Fraud Detection, Customer Analytics, Recommendation Engines, Risk & Compliance Management, Route Optimization and Others. In 2022, the fraud analytics segment accounted for the largest share of the graph analytics market. This segment's growth is being driven by the increasing adoption of technologies such as AI and machine learning for fraud detection. Furthermore, the rapid adoption of virtualization for big data analytics and the growing adoption of disruptive technologies are increasing the importance of fraud analytics.

By Industry Vertical: The report provides the bifurcation of the market into into nine segments based on the industry vertical: Banking, Financial Services and Insurance (BFSI), IT & telecom, manufacturing, healthcare, government, retail & e-commerce, education, transportation and others. In 2022, BFSI hold a dominant position in the graph analytics market to gain insights into customer behavior, detect fraud, manage risks, and enhance operational efficiency. BFSI companies also use graph analytics for credit risk analysis, customer segmentation, and predicting financial market trends. The factors driving the adoption of graph analytics in BFSI include the need to improve risk management, compliance with regulations, and the increasing volume of financial data generated.

By Region: The report provides insight into the graph analytics market based on the geographical operations, namely North America, Europe, Asia Pacific, Middle East & Africa and Latin America. The North American region held a dominant share in the graph analytics market, owing to the factors such as increasing adoption of cloud-based technologies, which are enabling businesses to store and analyze large amounts of data more efficiently and cost-effectively. Additionally, the growing importance of data-driven decision making in businesses is also fueling the demand for graph analytics solutions.

During the forecast period, Asia-Pacific is anticipated to expand rapidly. The region's rapid growth is primarily driven by the increasing adoption of technologies such as AI, big data, and IoT. Furthermore, rising corporate investments in real-time analytics, favourable government policies and regulations, and increased demand for data storage and security are expected to help the region grow at a rapid pace in the coming years.

Market Dynamics:

Growth Drivers: One of the most important factors impacting the global graph analytics market is the increasing availability of cloud-based analytics platforms. Cloud-based analytics platforms provide users with easy access to powerful graph analytics tools without the need for expensive hardware or software investments. This has made graph analytics more accessible to a wider range of users, including small and medium-sized businesses that may not have the resources to invest in their own infrastructure. Moreover, Cloud-based analytics platforms enable teams to collaborate on graph analytics projects in real-time, regardless of their location. This facilitates faster decision-making and enables organizations to more quickly respond to changes in the market or industry. Thus, the availability of cloud-based analytics platforms is driving the growth of the graph analytics market by providing users with easy access to powerful, scalable, and flexible analytics tools. Furthermore, the market has been growing over the past few years, due to factors such as surge in adoption of machine learning, increasing amount of data, rise in the demand for low latency queries, increasing adoption of big data analytics in various industries, increasingly complex data sets and many other factors.

Challenges: However, the market has been confronted with some challenges specifically, data privacy and security issues, lack of technical skills and lack of ease in programming and standardization, etc. Data privacy and security issues are important factors that can hamper the growth of the graph analytics market. Graph analytics involves the analysis of relationships and patterns within data sets. This type of analysis requires access to large amounts of data, which can include sensitive information. Companies must ensure that they comply with legal and regulatory requirements, implement robust cyber-security measures, maintain consumer trust and confidence, ensure data accuracy and quality, and manage the cost and complexity associated with these challenges.

Trends: The market is projected to grow at a fast pace during the forecast period, due to various latest trends such as growing volume of internet of things (IoT) Devices, emerging trends of social media analytics, increasing adoption of open-source graph databases, growing demand for fraud detection & expansion of use cases and increasing adoption of graph AI. The growing volume of Internet of Things (IoT) devices can have a significant impact on the graph analytics market. IoT devices generate massive amounts of data, which is often stored in graphs, making it easier to extract insights from the data. Graph analytics can be used to process this data and uncover patterns, relationships, and anomalies, providing valuable insights to businesses and organizations. As the number of IoT devices continues to grow, the volume of data generated by these devices will also increase exponentially. This means that there will be an increasing demand for advanced graph analytics tools that can handle the large volumes of data and provide real-time insights. This presents a huge opportunity for graph analytics vendors to develop new and innovative solutions that can help organizations extract insights from IoT data.

Impact Analysis of COVID-19 and Way Forward:

The COVID-19 pandemic has accelerated the adoption of graph analytics solutions across various industries, as companies look for ways to improve their operational efficiency, reduce costs, and gain insights into customer behavior. One of the biggest impacts of COVID-19 on the graph analytics market has been the increased demand for cloud-based solutions. The pandemic has accelerated the shift to the cloud, as organizations seek to leverage the scalability and flexibility of cloud-based solutions to meet the changing demands of their businesses. Cloud-based graph analytics solutions offer several advantages, including faster deployment, lower costs, and easier integration with other cloud-based applications.

The healthcare industry has also seen a significant impact from COVID-19 on the graph analytics market. The pandemic has highlighted the importance of data and analytics in healthcare, as healthcare providers have needed to quickly analyze large amounts of data related to the spread of the virus and the effectiveness of different treatments. Overall, while the COVID-19 pandemic has created many challenges for businesses around the world, it has also highlighted the importance of graph analytics in helping companies to navigate uncertain times and make informed decisions. As a result, the global graph analytics market is expected to continue to grow in the years to come.

Competitive Landscape:

The global graph analytics market is highly fragmented due to the presence of many small and medium-sized companies competing with each other and large enterprises. Technological advancements in the market are also bringing sustainable competitive advantage to companies, and the market is witnessing multiple partnerships and mergers.

The key players in the global graph analytics market are:

Oracle Corporation
Microsoft Corporation
IBM Corporation
Neo4j, Inc.
TigerGraph, Inc
TIBCO Software, Inc.
Lynx Analytics
Tom Sawyer Software
Datastax, Inc
Kineviz, Inc.
Expero, Inc
Linkurious SAS
Graphistry

Global Graph Analytics Market: Analysis By Component (Solutions & Services), By Deployment (On Premise & Cloud), By Enterprise Size (Large Enterprises and Small and Medium Enterprises (SMEs)), By Application (Fraud Detection, Customer Analytics, Recommendation Engines, Risk & Compliance Management, Route Optimization & Others), By Industry Vertical (Banking, Financial Services and Insurance (BFSI), IT & Telecom, Manufacturing, Healthcare, Government, Retail & E-commerce, Education, Transportation & Others), By Region, Size and Trends with Impact of COVID-19 and Forecast up to 2028 - Report Summary

Report Metrics	Details
Years Considered	2018-2028
Base Year	2022
Forecast Period	2023-2028
Page Count	177
Units Referenced	US $
Segments/Key Topics	By Component, By Deployment, By Enterprise Size, By Application, By Industry Vertical
Key Companies Mentioned	Oracle Corporation, Microsoft Corporation, IBM Corporation, Neo4j, Inc., TigerGraph, Inc., TIBCO Software, Inc., Lynx Analytics, Tom Sawyer Software, Datastax, Inc., Kineviz, Inc., Expero, Inc., Linkurious SAS, and Graphistry

Five FAQs about the Report

What is the size of this market?
The global graph analytics market in 2022 was valued at US$1.14 billion.

What is the forecasted growth for this market?
The market would reach US$6.90 billion by 2028, growing at a CAGR of 34.80%, during the forecast period of 2023-2028.
9What are key factors driving this market?
The graph analytics market's steady growth can be attributed primarily to a surge in demand for real-time insights with data visualization, growing need to analyze low-latency graph queries, and the emergence of disruptive technologies. Furthermore, the growing demand for real-time analysis and identification of complex patterns, as well as the growing use of big data virtualization, are creating new growth opportunities for graph analytics vendors. Improved performance, scalability, reliability, better problem solving, and real-time application are some of the key benefits of implementing graph analytics solutions.

How is this market segmented in this report?
In the report, the global graph analytics market is segmented based on component (solutions & services), deployment (on premise & cloud), enterprise size (large enterprises and small and medium enterprises (SMEs)), application (fraud detection, customer analytics, recommendation engines, risk & compliance management, route optimization & others), and industry vertical (banking, financial services and insurance (BFSI), IT & telecom, manufacturing, healthcare, government, retail & e-commerce, education, transportation & others).

What is the definition of this market in this report?
Graph analytics is a set of analytical techniques that are used to examine the relationships between entities in a graph or network structure. A graph is a collection of nodes, or vertices, connected by edges, or relationships. Graph analytics can help to uncover patterns, insights, and anomalies in the data, and can be used to make better decisions, improve processes, and create new products and services. Graph analytics helps organizations to understand relationships between complex and constantly changing data, to extract insights in real time and deliver actionable information, allowing businesses to respond to trends and emerging issues proactively and with full context.

What are the major influences driving the growth/decline of this market?
The global graph analytics market growth is predicted to be supported by increasing availability of cloud-based analytics platforms, surge in adoption of machine learning, increasing amount of data, rise in the demand for low latency queries, increasing adoption of big data analytics in various industries and increasingly complex data sets. Conversely, the market growth would be negatively impacted by various challenges such as data privacy and security issues, lack of technical skills and lack of ease in programming and standardization.