Graph Database Market to grow USD 7.3 billion by 2028

"The demand for graph database tools has witnessed a tremendous shift due to the growing trends of Artificial Intelligence (AI), real-time big data, and increase adoption of cloud.The graph database is a platform for storing, querying, and modifying network graphs. A network graph is a graphical representation of nodes and edges. Each node represents an entity (for instance, a person), and each edge represents a link or relationship between two nodes. "

The global market size to grow from USD 2.9 billion in 2023 to USD 7.3 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 20.2% during the forecast period. Graph databases find their applications in linguistics, chemistry, and social networks. For instance, the integration of technology enables the user to demonstrate the relationship between people and their organizations. Companies operating in the market have come up with several use cases to describe specific graph database applications in multiple industry verticals. One such instance is fraud detection using the graph database technology developed by Ravelin Technology. Ravelin visualizes graph databases to identify suspicious nodes. The company has developed its own proprietary graph database solution to generate a full graph for any given data set in single-digit microseconds.

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The cloud segment to have the largest CAGR during the forecast period

By deployment mode, the graph database market has been segmented into on-premises and cloud. The CAGR of the cloud deployment mode is estimated to be the largest during the forecast period. The cloud-based deployment helps businesses more efficiently process and report data findings, enhance collaboration, and enable decision-makers to get faster access to business intelligence leading to its higher adoption in the graph database market.

The native graph database segment to have the largest CAGR during the forecast period

Native graph database is a specialized database management system designed to efficiently store, manage, and query graph-structured data, where entities (nodes) are connected by relationships (edges). Unlike traditional relational databases, native graph databases are optimized for traversing complex relationships and performing graph-oriented queries. They enable the representation of real-world connections in a more intuitive and natural manner, making them particularly well-suited for use cases like social networks, recommendation systems, fraud detection, and knowledge graphs.

The healthcare, pharmaceuticals, and life sciences segment to have the largest CAGR during the forecast period

Graph databases offer significant advantages to the healthcare, pharmaceutical, and life sciences sectors due to their ability to model and query complex relationships within data. Graph databases can help researchers identify potential drug targets by analyzing the interactions between proteins, genes, and pathways. Relationships between proteins and diseases can be modeled, aiding in the validation of therapeutic targets.

Among regions, APAC to hold higher CAGR during the forecast period

APAC is expected to grow at a good pace during the forecast period. Opportunities for smaller graph database vendors to introduce graph database solutions for numerous sectors have also increased. All these factors are responsible for the expeditious growth of the graph database market in the region. Companies operating in APAC continue to focus on improving customer services to drive market competitiveness and revenue growth. China, Japan,India, and ANZ have displayed ample growth opportunities in the graph database market.

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