Market Analysis and Insights:
The market for Graph Database was estimated to be worth USD 2.12 billion in 2022, and from 2023 to 2032, it is anticipated to grow at a CAGR of 16.45%, with an expected value of USD 10.30 billion in 2032.
The market for Graph Databases is experiencing notable growth driven by various key factors. An essential factor is the widespread adoption of graph databases across sectors like healthcare, retail, manufacturing, and transportation. These databases are proving instrumental in enhancing data management and analysis capabilities by effectively representing intricate relationships among diverse data components. Another crucial driver is the increasing need for instantaneous data processing and analysis, drawing attention to graph databases for their high-performance features in handling extensive interconnected datasets. Further fueling market growth is the escalating emphasis on data-centric decision-making within organizations, as graph databases empower enhanced insights and predictive analytical capabilities. Moreover, the continuous technological progressions, notably in cloud computing and big data analytics, are contributing significantly to market expansion. The growing accessibility of open-source graph database solutions is icularly appealing to small and medium-sized enterprises, amplifying market growth. Nonetheless, challenges relating to data security, privacy concerns, and the complexity associated with implementing graph databases could pose some limitations to market advancement. Overall, the graph database market is poised for substantial growth in the foreseeable future, propelled by the influential factors mentioned.
Graph Database Market Scope:
| Metrics | Details |
| Base Year | 2023 |
| Historic Data | 2018-2022 |
| Forecast Period | 2024-2032 |
| Study Period | 2018-2032 |
| Forecast Unit | Value (USD) |
| Revenue forecast in 2032 | USD 10.30 billion |
| Growth Rate | CAGR of 16.45% during 2023-2032 |
| Segment Covered | By Component, By Type, By Analysis Type, By Application, By Deployment, By Application, By End User, By Region. |
| Regions Covered | North America, Europe, Asia Pacific, South America, Middle East and Africa |
| Key Players Profiled | Neo4j Inc., Microsoft Corporation, IBM Corporation, Amazon Web Services, Oracle Corporation, OrientDB (as the prime supporter of the OrientDB project), MarkLogic Corporation, ArangoDB GmbH, DataStax Inc., and Franz Inc. |
Market Definition
A graph database is a specialized database that employs graph structures for data representation, storage, and retrieval. In this database model, the significance of relationships between entities is emphasized equally with the entities themselves. Unlike conventional relational databases, graph databases excel in navigating intricate connections and relationships with high efficiency. Graph databases have gained significance for their efficiency in storing and analyzing intricate relationships among data points. In contrast to conventional relational databases that employ tables, graph databases employ nodes and edges to depict connections and interactions. This characteristic makes them icularly suitable for applications like social networks, recommendation systems, and fraud detection, where comprehending the relationships between entities is essential for valuable insights. Moreover, graph databases facilitate swift traversal and retrieval of interconnected data, ensuring superior performance and scalability. Thus, with their capacity to manage complex relationships and deliver actionable insights, graph databases have emerged as a crucial component in the contemporary data-centric landscape.
Key Market Segmentation:
Insights On Key Component
Software
Software is expected to dominate the Global Graph Database Market.
This can be attributed to the growing demand for advanced data management and analysis solutions. With the increasing need for processing complex and interconnected data, graph database software provides efficient and scalable solutions. It enables organizations to store, query, and analyze large volumes of data with complex relationships, making it ideal for applications such as fraud detection, recommendation engines, and social network analysis.
Additionally, the availability of various graph database software options, including open-source and commercial solutions, further drives the dominance of this .
Services
Services also holds significant importance in the Global Graph Database Market. Services play a crucial role in supporting the implementation, integration, and maintenance of graph database solutions. Organizations often require professional services, such as consulting, training, and support, to effectively deploy and leverage graph databases within their existing infrastructure. Service providers offer expertise and assistance in areas like data modeling, query optimization, and performance tuning, ensuring successful implementation and optimal utilization of graph database technology. Consequently, the Services complements the dominance of the Software , collectively driving the growth of the Global Graph Database Market.
Insights On Key Type
Relational (SQL)
The Relational (SQL) is expected to dominate the Global Graph Database Market. SQL-based graph databases offer the advantage of levering existing relational database management systems (RDBMS) infrastructure and expertise. This allows for the efficient storage and retrieval of interconnected data using SQL queries, making it suitable for complex data relationships and large-scale graph applications. With its established use cases, widespread adoption, and mature technology, Relational (SQL) graph databases are likely to dominate the market.
Non-Relational (NoSQL)
The Non-Relational (NoSQL) , while not expected to dominate the Global Graph Database Market, still holds significant market presence and growth potential. NoSQL graph databases provide flexibility and scalability for handling large volumes of interconnected data, making them suitable for real-time applications, social networks, and recommendation systems. With their schema-less architecture, NoSQL graph databases enable developers to easily adapt and modify data models as needed. While Relational (SQL) graph databases may dominate due to their wider adoption and maturity, the Non-Relational (NoSQL) is anticipated to continue its growth trajectory and play a vital role in specific use cases.
Insights On Key Analysis Type
Connectivity Analysis is expected to dominate the Global Graph Database Market. Connectivity analysis plays a crucial role in graph database systems as it focuses on the relationships and connections between data points. By analyzing the connectivity patterns, businesses can uncover hidden insights, identify trends, and improve decision-making processes. This enables companies to understand the interconnections within their data, identify clusters or communities, and explore the dynamics of relationships. With the increasing adoption of graph database technology and the need for analyzing complex and connected data, connectivity analysis is likely to dominate the Global Graph Database Market.
Community Analysis:
Community analysis is another key segment the graph database market. It helps in identifying communities or groups of related data points within a dataset. By leveraging community analysis, organizations can gain insights into social networks, user communities, or clusters of similar objects. While community analysis provides valuable data for various applications such as social media analytics or fraud detection, it may not have the same level of dominance as connectivity analysis.
Centrality Analysis:
Centrality analysis focuses on understanding the importance or influence of specific nodes within a graph. By measuring centrality metrics such as degree centrality, betweenness centrality, or closeness centrality, businesses can identify key entities, influencers, or critical points in a network. Despite its significance in identifying pivotal nodes, centrality analysis may not dominate the Global Graph Database Market as it serves a specific purpose rather than being widely applicable to various industries.
Path Analysis:
Path analysis involves studying the ways in which nodes are connected within a graph database. It focuses on finding the shortest or most relevant paths between two or more nodes, enabling businesses to analyze patterns, optimize routes, or identify bottlenecks. Although path analysis has its uses in transportation, logistics, or recommendation systems, it may not be expected to dominate the Global Graph Database Market due to its limited scope compared to connectivity analysis.
Insights On Key Deployment
Cloud
Cloud is expected to dominate the Global Graph Database Market.
This is primarily due to the numerous advantages offered by cloud deployment.Cloud-based graph databases provide scalability, flexibility, and cost-efficiency, making them the preferred choice for many organizations. With the growing trend of digital transformation and the increasing volume of data being generated, cloud deployment offers the ability to handle large datasets and support high-performance computing. Additionally, cloud-based solutions enable easy access to data from anywhere, facilitate collaboration among teams, and provide automatic updates and maintenance. As a result, the cloud is anticipated to dominate the Global Graph Database Market.
On Premise
On Premise still holds significance for certain industries and organizations. On Premise deployment offers benefits such as enhanced control over data, data privacy compliance, and the ability to customize and tailor the graph database solution according to specific requirements. Industries with strict data security regulations, or those in remote locations with limited internet connectivity, may prefer On Premise deployment. Furthermore, some organizations may have existing IT infrastructure and prefer to utilize their own resources. Although the dominance lies with the Cloud , On Premise deployment still remains a relevant choice for certain s of the market.
Insights On Key Application
Identity and Access Management:
Identity and Access Management is expected to dominate the Global Graph Database Market. With the increasing concern for data security and privacy, organizations are prioritizing identity and access management solutions to ensure secure access to sensitive information. Graph databases provide a highly efficient and flexible way to manage and analyze complex relationships between various user identities and their access rights. This enables organizations to have a comprehensive view of user access patterns and detect any potential security threats. Therefore, Identity and Access Management is expected to be the leading in the Global Graph Database Market.
Customer Analytics:
Customer Analytics is another important in the Global Graph Database Market. With the rise of big data and the need to understand customer behavior and preferences, organizations are leveraging graph databases to gain insights from complex and interconnected customer data. Graph databases enable businesses to uncover valuable patterns, relationships, and connections within customer data, helping them make data-driven decisions and improve customer satisfaction. As a result, Customer Analytics is expected to have a significant impact on the Global Graph Database Market.
Recommendation Engine:
Recommendation Engine is expected to play a crucial role in the Global Graph Database Market. Recommendation engines heavily rely on graph databases to analyze and make personalized recommendations based on the connections between users, items, and their attributes. By utilizing graph databases, recommendation engines can provide accurate and relevant product recommendations, enhance customer experience, and drive sales. Thus, the Recommendation Engine is set to have a strong presence in the Global Graph Database Market.
Master Data Management:
Master Data Management is expected to hold a notable position in the Global Graph Database Market. As organizations deal with vast volumes of data from various sources, they require efficient methods to manage and integrate their master data. Graph databases offer a powerful approach to modeling complex relationships across diverse data domains, enabling effective master data management. By leveraging graph databases, organizations can achieve data consistency, accuracy, and reliability, which are vital for decision-making and operational efficiency.
Privacy and Risk Compliance:
In the Global Graph Database Market, Privacy and Risk Compliance is anticipated to have a significant impact. With the increasing emphasis on data privacy regulations, organizations need robust tools to ensure compliance with stringent privacy laws and mitigate risk. Graph databases provide a comprehensive framework for managing sensitive data and enforcing privacy controls. By leveraging graph databases, organizations can track and trace data lineage, monitor data accesses, and maintain auditable data records, thus facilitating compliance with privacy regulations and minimizing the risk of data breaches.
Fraud Detection and Risk Management:
Fraud Detection and Risk Management is expected to contribute significantly to the Global Graph Database Market. Fraud detection and risk management require the analysis of complex networks of transactions, entities, and activities to identify suspicious patterns and anomalies. Graph databases offer the capability to model and query these intricate relationships effectively. By utilizing graph databases, organizations can detect and prevent fraudulent activities, enhance fraud investigation processes, and improve overall risk management strategies.
Others:
The "Others" represents various applications that are not explicitly mentioned in the given list. These applications could include diverse use cases such as supply chain management, social network analysis, knowledge graph development, and many more. While the specific dominance of any icular application in this cannot be determined without further data and analysis, it is essential to acknowledge the potential for various other applications to contribute to the Global Graph Database Market.
Insights On Key End User
Banking
The banking sector is expected to dominate the global graph database market. This is due to the increasing need for data management and analysis in the banking industry. Graph databases provide robust capabilities for managing complex relationships and interconnected data, which is crucial for banks dealing with vast amounts of customer data, transactions, and networks. With the adoption of digital technologies and the rise of fintech, banks are leveraging graph databases to enhance fraud detection, risk assessment, customer relationship management, and compliance monitoring. The banking sector's reliance on data-driven decision making and its continuous quest for innovation positions it as the dominating in the global graph database market.
IT & Telecommunication
The IT & Telecommunication sector is another significant in the global graph database market. As the industry evolves and becomes more data-intensive, graph databases offer valuable solutions for managing and analyzing the complex relationships and hierarchies within telecommunications networks, infrastructure, and customer data. IT companies and telecom operators leverage graph databases to optimize network performance, troubleshoot connectivity issues, analyze customer behavior, and provide personalized services. The high volume of data generated by the IT & Telecommunication sector, along with the need for real-time insights and efficient data management, makes it a key player in the graph database market.
Retail
The retail sector has also emerged as a prominent in the global graph database market. With the increasing demand for personalized shopping experiences, efficient supply chain management, and effective customer engagement, retailers are turning to graph databases to harness the power of connected data. By leveraging graph databases, retailers can uncover patterns, associations, and insights from vast datasets, enabling them to optimize inventory management, enhance customer recommendations, and identify market trends. The ability of graph databases to handle complex relationships and provide real-time data analysis makes it a valuable tool for the retail industry, positioning it as a significant in the market.
Healthcare
In the healthcare sector, graph databases play a crucial role in managing interconnected data and facilitating better patient care outcomes. The healthcare industry generates vast amounts of data from patient records, medical devices, research studies, and clinical trials. By adopting graph databases, healthcare providers can seamlessly integrate disparate data sources, identify patterns in patient outcomes, optimize treatment pathways, and improve population health management. With the growing emphasis on data-driven healthcare systems and precision medicine, the healthcare has become increasingly important in the global graph database market.
Life Science, Media & Entertainment, Government, Others While each of these sectors, namely Life Science, Media & Entertainment, Government, and Others, may have specific use cases for graph databases, they are not expected to dominate the global market. Life science organizations may utilize graph databases for drug discovery and genomics research, media and entertainment companies may employ them for content recommendation and audience analysis, governments may leverage them for social network analysis and public administration, and other industries may have their unique applications.
However, their overall market share is expected to be smaller compared to the dominant sectors mentioned earlier.
Insights on Regional Analysis:
Asia Pacific
Asia Pacific is expected to dominate the Global Graph Database market due to several factors. Firstly, the region is witnessing rapid technological advancements and digital transformation across various industries, including banking, retail, and healthcare. This has increased the demand for efficient data management solutions, including graph databases. Additionally, countries like China and India are experiencing substantial growth in the e-commerce sector, generating vast amounts of structured and unstructured data that need to be effectively analyzed and managed. Furthermore, Asia Pacific has a large pool of skilled IT professionals and a thriving startup ecosystem, which fosters innovation and the adoption of advanced technologies. These factors, coupled with the growing emphasis on data-driven decision-making, are expected to drive the dominance of Asia Pacific in the Global Graph Database market.
North America
North America is a major player in the Global Graph Database market due to its highly developed IT infrastructure, strong presence of tech giants, and early adoption of cutting-edge technologies. The region has a significant concentration of key players offering graph database solutions, which attracts a large customer base. With industries like financial services, healthcare, and e-commerce extensively leveraging data analytics and artificial intelligence, the need for efficient data management solutions is high. Additionally, North America is home to numerous research and development centers, fostering innovation and driving advancements in the field of graph databases. Overall, these factors contribute to the dominance of North America in the Global Graph Database market.
Europe
Europe is poised to play a significant role in the Global Graph Database market. The region has a mature IT landscape and is known for its strong focus on data privacy and security, making it a suitable market for graph database solutions that offer robust data management capabilities. Moreover, European countries have witnessed a surge in digital transformation initiatives across industries such as manufacturing, logistics, and telecommunications. As a result, there is a growing demand for advanced data analytics tools, including graph databases, to unlock valuable insights from complex interconnected data. Additionally, Europe has a well-established startup ecosystem and academic institutions that contribute to technological innovation. These factors contribute to Europe's potential to dominate the Global Graph Database market.
Middle East & Africa
The Middle East & Africa region is expected to witness significant growth in the Global Graph Database market. The region has been investing heavily in digital transformation initiatives, with a icular focus on sectors like government, healthcare, and finance. Graph databases offer unique capabilities to manage complex data structures prevalent in these industries, enabling efficient data analysis and decision-making. Furthermore, there is a growing emphasis on data privacy and cybersecurity in the region, driving the adoption of advanced data management solutions. Additionally, the Middle East & Africa has a rising startup ecosystem and is attracting investments in the technology sector, which encourages the adoption of innovative solutions like graph databases. These factors indicate the potential for the region to dominate the Global Graph Database market.
Latin America
Latin America is emerging as a key player in the Global Graph Database market. The region has been experiencing digital transformation across various industries, driven by increased internet penetration, smartphone adoption, and the growth of e-commerce. This has resulted in a massive volume of data being generated, calling for efficient data management solutions like graph databases. Moreover, Latin American countries are witnessing rapid urbanization and the establishment of smart cities, leading to a need for sophisticated data analytics tools to manage complex urban systems. Furthermore, the region is home to a growing number of startups and technology hubs, fostering innovation and driving the adoption of advanced technologies. These factors position Latin America to have a significant presence in the Global Graph Database market.
Company Profiles:
Prominent figures within the Global Graph Database sector specialize in creating and delivering advanced graph database platforms that enable enterprises to effectively store, handle, and interpret intricate data connections. They are dedicated to ongoing innovation and product refinement to cater to the changing requirements of businesses operating in diverse fields.
Leading figures in the graph database sector comprise Neo4j Inc., Microsoft Corporation, IBM Corporation, Amazon Web Services, Oracle Corporation, OrientDB (as the prime supporter of the OrientDB project), MarkLogic Corporation, ArangoDB GmbH, DataStax Inc., and Franz Inc. These prominent entities lead the way in designing and delivering innovative graph database solutions to meet the increasing need for effective data management systems. Their diverse range of offerings aims at optimizing data processing and analytical capabilities, refining decision-making procedures, and empowering enterprises to extract valuable insights from interconnected data relationships. By leveraging their profound knowledge of graph technology, these key actors significantly contribute to bolstering the acceptance and utilization of graph databases across diverse sectors.
COVID-19 Impact and Market Status:
The worldwide market for graph databases is currently being influenced by the Covid-19 pandemic, leading to a variety of trends and changes in how graph database solutions are being utilized.
The global landscape of the graph database market has been influenced by the COVID-19 pandemic in both favorable and adverse ways. The widespread transition to remote work has driven a surge in the demand for cloud-based services and data management platforms, benefiting graph databases known for their proficiency in managing intricate and interconnected data sets. Businesses spanning various sectors including healthcare, finance, and e-commerce have acknowledged the significance of utilizing graph databases to extract insights from their data and enhance operational efficiency. Conversely, the economic challenges brought about by the pandemic have prompted budget restrictions for numerous companies, leading to delays or cancellations of specific IT initiatives and potentially impacting the integration of graph databases. Nevertheless, the future outlook for the graph database market remains optimistic, as organizations increasingly recognize the necessity of scalable and adaptable data management solutions to facilitate their digital transformation endeavors in a post-pandemic era.
Latest Trends and Innovation:
- In September 2021, Neo4j, a leading graph database company, announced a nership with Syniti, a global data solution provider, to improve data integration and migration for enterprises.
- In May 2021, TigerGraph, a popular graph analytics platform, secured $105 million in Series C funding to accelerate its global expansion and strengthen its product offerings.
- In April 2021, Amazon Neptune, a fully-managed graph database service, introduced new features including point-in-time recovery, cross-region read replicas, and enhanced security capabilities
- In March 2021, DataStax, an open-source data platform, launched DSE 6.8, which includes improved graph database performance and deeper integration with analytics tools.
- In February 2021, Microsoft announced the general availability of Azure Cosmos DB's Gremlin API, enabling developers to build and deploy graph applications using the popular Apache TinkerPop framework.
- In December 2020, MongoDB, a leading modern database platform, unveiled MongoDB 4.4 with native graph capabilities, allowing users to efficiently model, analyze, and traverse connected data.
- In September 2020, OrientDB, an open-source multi-model database, was acquired by CallidusCloud, a provider of sales performance management software, enabling enhanced graph database functionality within their platform.
- In June 2020, JanusGraph, an open-source distributed graph database, released version 0.5.2 with improved query performance, expanded data modeling options, and enhanced security features.
- In May 2020, ArangoDB, a native multi-model database, introduced the ArangoDB Oasis platform, offering fully-managed graph database as a service to simplify deployment and management for users.
- In February 2020, TigerGraph announced the availability of TigerGraph Cloud on AWS Marketplace, enabling users to easily access and deploy their graph database platform on Amazon Web Services.
Significant Growth Factors:
Factors driving the expansion of the Graph Database Market encompass the growing need for instantaneous data analysis, escalating uptake of big data analytics, and the advent of sophisticated technologies such as artificial intelligence (AI) and Internet of Things (IoT). The market for graph databases is poised for significant growth in the upcoming years, mainly driven by multiple key factors. One prominent factor is the escalating need for real-time data analysis and insights, which is propelling the uptake of graph databases. These databases offer a more effective mechanism for storing and analyzing interconnected data, empowering organizations to swiftly extract valuable insights. Another contributing factor is the increasing prominence of social networks and the necessity to manage intricate relationships between entities like users, companies, and products, driving the demand for graph databases. Graph databases specialize in representing and analyzing these relationships, positioning them as a preferred option for social network analysis and recommendation systems. Furthermore, as the utilization of Internet of Things (IoT) devices continues to surge, massive volumes of data with complex relationships are being generated, challenging traditional databases. Graph databases, characterized by their capability to model and query intricate interconnected data effortlessly, are emerging as a viable solution for managing IoT data.
Additionally, the rising need for fraud detection and risk analysis spanning across diverse industries is fostering the adoption of graph databases. These databases equip advanced analytical functionalities to identify and thwart fraud by scrutinizing complex relationships and patterns. Given the increasing emphasis on data-centric decision-making, the graph database market is poised for substantial growth in the foreseeable future. Nevertheless, factors such as data privacy and security apprehensions, coupled with the demand for skilled professionals, may present hurdles to the market's growth.
Restraining Factors:
The Graph Database Market faces constraints in its growth due to the limited uptake by conventional organizations and the requirement for technical proficiency during implementation.The market for graph databases is showing notable growth due to the rising adoption of this technology across diverse industries.
Nevertheless, certain factors are restricting the market's full potential. The intricate nature and learning curve linked with graph databases can present a significant hurdle for businesses. The implementation and management of these databases require specialized skills, which can be challenging for organizations lacking the necessary expertise. Furthermore, a lack of awareness and understanding regarding the advantages and applications of graph databases among a substantial number of potential users is constraining market expansion. Many organizations continue to depend on traditional relational databases and are hesitant to invest in transitioning to graph databases. Furthermore, apprehensions about data security and privacy pose another substantial restraint on the market. Since graph databases store interconnected data, ensuring the confidentiality and safeguarding of sensitive information is vital. Finally, the high initial investment and upkeep expenses associated with graph databases can discourage small and medium-sized enterprises from embracing this technology. Despite these obstacles, the graph database market still harbors significant potential. As businesses increasingly acknowledge the benefits of utilizing interconnected data for intricate analytics and data-driven decision-making, the demand for graph databases is projected to increase. With continuous technological advancements and growing awareness, organizations are likely to surmount current limitations and propel the future expansion of the graph database market.
Key Segmentation:
Component Overview
• Software
• Services
Type Overview
• Relational (SQL)
• Non-Relational (NoSQL)
Analysis Type Overview
• Community Analysis
• Connectivity Analysis
• Centrality Analysis
• Path Analysis
Deployment Overview
• Cloud
• On Premise
Application Overview
• Identity and Access Management
• Customer Analytics
• Recommendation Engine
• Master Data Management
• Privacy and Risk Compliance
• Fraud Detection and Risk Management
• Others
End User Overview
• Banking, Financial Services and Insurance (BFSI)
• IT & Telecommunication
• Retail
• Healthcare
• Life Science
• Media & Entertainment
• Government
• Others
Regional Overview
North America
• US
• Canada
• Mexico
Europe
• Germany
• France
• U.K
• Rest of Europe
Asia Pacific
• China
• Japan
• India
• Rest of Asia Pacific
Middle East and Africa
• Saudi Arabia
• UAE
• Rest of Middle East and Africa
Latin America
• Brazil
• Argentina
• Rest of Latin America
Frequently Asked Questions (FAQ) :
The market value of graph database market in 2032 was USD 10.30 billion.
The major contenders in the global graph database market Neo4j Inc., Microsoft Corporation, IBM Corporation, Amazon Web Services, Oracle Corporation, OrientDB (as the prime supporter of the OrientDB project), MarkLogic Corporation, ArangoDB GmbH, DataStax Inc., and Franz Inc.
The base year for the report is 2023 in graph database market.
Wide range of applications for graph databases across social networks, linguistics, and chemistry is fueling the industry growth. On the other hand, rising integration of technologies, which determines issues and use cases is also increasing the need for graph database. These systems elaborate specific graph database applications in several verticals. It can be helpful in various social networks comprising the genomic sequencing, recommendation engines, and logistics. The enterprise operating within the industry offer radically new approaches to connect millions of sets of connected data, link heterogeneous information, enhance operational agility for customer service, and create new sources for customer value.
Type Segment
Based on the component segment, the market is bifurcated into RDF, and property graph. In 2019, the property graph segment gathered the largest market revenue and it is anticipated to govern the graph database market throughout the forecast period. However, the RDF segment is anticipated to grow at a substantial growth rate over the forecast period.
Application Segment
Based on the application, the market is segmented into customer analytics, risk and compliance management, recommendation engines, fraud detection, supply chain management, and others. The market for recommendation engines is anticipated to possess a significant market share in 2019. However, the customer analytics segment is likely to grow with a significant growth rate since the small & medium enterprises today are predominantly developing to match their user needs.
Vertical Segment
Based on the vertical, the market is segmented into telecom & IT, BFSI, retail, government & utilities, media & entertainment, healthcare, manufacturing, and others. The market for BFSI sector is anticipated to possess the highest growth rate over the forecast period since the need for graph database find a wide applications in banking, finance & insurance companies for cash flow analysis, fraud detection, and transaction analysis. Moreover, the growing regulatory scrutiny coupled with enhanced customer satisfaction, as well as advantages such as risk management, and customized solutions are some of the factors responsible for the graph database demand.
The global graph database market is a wide range to North America, Europe, APAC, South America, and the Middle East & Africa. North America is considered a mature market in the graph database storage, owing to an outsized presence of organization with the availability of technical expertise and advanced IT infrastructure. The United States and Canada are the highest contributory nations to the expansion of the graph database market in North America.
The major players of the global graph database market are IBM, Oracle, AWS, Microsoft, Neo4j, OrientDB, Franz, OpenLink Software, TIBCO, MarkLogic, DataStax, Ontotext, Stardog, TigerGraph, Cray, and more. The graph database market is fragmented with the existence of well-known global and domestic players across the globe.