Apr 24, 2023

News provided by Share this article Share this article 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. The market value is expected to grow at a CAGR of 34.80% during the forecast period of 2023-2028. 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 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 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. 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. Market Dynamics Increasing Amount Of Data Increasing Adoption Of Big Data Analytics In Various Industries Increasingly Complex Data Sets