Graph Analytics

Graph Analytics Market Outlook

The global graph analytics market is poised for significant growth, projected to reach USD 8 billion by 2035, exhibiting a remarkable compound annual growth rate (CAGR) of 30.1% during the forecast period from 2025 to 2035. This expansion can primarily be attributed to the increasing volume of data generated across various sectors, necessitating sophisticated methods for data analysis and visualization. As organizations strive to derive actionable insights from complex interconnected data, the demand for graph analytics solutions is surging. Additionally, the rise of artificial intelligence (AI) and machine learning (ML) technologies is further augmenting market growth, as these solutions enhance data processing capabilities and provide deeper insights into patterns and relationships within datasets. Moreover, the growing emphasis on customer experience and data-driven decision-making is propelling businesses to adopt graph analytics solutions for improved data management and strategic planning.

Growth Factor of the Market

The growth of the graph analytics market can be attributed to several key factors that are reshaping the landscape of data analysis. Firstly, the exponential increase in data generation, fueled by digital transformation across industries, creates a pressing need for advanced analytical tools. Graph analytics enables organizations to visualize and understand complex relationships and networks, thereby unlocking new insights that traditional analytical methods often overlook. Secondly, industries such as BFSI, retail, and healthcare are increasingly leveraging graph analytics for fraud detection, risk management, and personalized customer interactions, further driving market demand. Thirdly, the rise of interconnected systems and the Internet of Things (IoT) has generated a wealth of relational data, which graph analytics can effectively process to reveal significant insights and trends. Additionally, the integration of artificial intelligence and machine learning technologies in graph analytics platforms enhances the predictive capabilities of these solutions, making them indispensable for businesses seeking competitive advantages. Finally, the growing trend of cloud-based solutions is facilitating the adoption of graph analytics tools, particularly among small and medium-sized enterprises that require scalable and cost-effective options.

Key Highlights of the Market

• The market is expected to reach USD 8 billion by 2035, with a CAGR of 30.1% from 2025 to 2035.
• Rapid digital transformation and increasing data generation are primary drivers of market growth.
• Graph analytics is increasingly utilized in sectors like BFSI, retail, and healthcare for fraud detection and customer insights.
• The integration of AI and ML into graph analytics platforms enhances predictive analytics capabilities.
• Cloud-based graph analytics solutions are gaining traction among small and medium-sized enterprises for their scalability.

By Component

Software :

The software segment of the graph analytics market encompasses various tools and platforms specifically designed to analyze and visualize graph data. Organizations utilize graph analytics software to model relationships between different data points, which enables them to uncover hidden patterns and insights that are crucial for decision-making. These tools come with advanced algorithms that facilitate complex queries and analyses, allowing users to explore massive datasets efficiently. As businesses increasingly seek to harness the power of big data, the demand for sophisticated graph analytics software continues to grow. Moreover, the integration of AI capabilities into these software solutions allows for enhanced predictive analytics, making them essential for a wide range of applications, including network analysis, social media analytics, and customer relationship management. The continuous evolution of software features, updates, and enhancements also plays a pivotal role in driving the adoption of graph analytics software across industries.

Services :

The services segment within the graph analytics market includes consulting, implementation, and support services that assist organizations in effectively utilizing graph analytics solutions. As graph analytics can be complex, many businesses seek expert guidance to ensure successful deployment and optimization of the technology. Consulting services help organizations understand their specific needs and how graph analytics can be integrated into their existing systems. Implementation services facilitate the deployment of graph analytics tools tailored to an organization's unique requirements, ensuring that the technology is used to its fullest potential. Additionally, ongoing support services are critical for maintaining the performance of these solutions, providing troubleshooting assistance, updates, and training for users. The increasing reliance on data-driven decision-making is fueling demand for comprehensive services that accompany graph analytics software, thereby boosting the overall growth of this segment.

By Deployment Mode

On-Premises :

The on-premises deployment mode for graph analytics solutions allows organizations to host their data and analytics tools within their own infrastructure. This approach is preferred by many large enterprises concerned about data security and compliance with industry regulations. With on-premises deployment, companies have complete control over their data, enabling them to implement their security protocols effectively and manage data access. However, the initial investment for on-premises solutions can be substantial due to the need for hardware and maintenance. Despite the costs, many organizations value the benefits of customizability and the ability to integrate graph analytics into their existing systems seamlessly. As data privacy concerns continue to rise, the on-premises deployment mode is likely to maintain its relevance, particularly among industries with stringent regulatory requirements.

Cloud :

Cloud deployment of graph analytics has gained immense popularity due to its flexibility, scalability, and cost-effectiveness. Organizations can access powerful graph analytics tools without the need for significant upfront investments in hardware, as cloud solutions operate on a subscription model. This deployment mode allows businesses to scale their analytics capabilities according to their changing needs, accommodating fluctuations in data volume and analysis requirements. Additionally, cloud-based graph analytics solutions often feature advanced functionalities and regular updates, providing users with the latest tools and technologies. The ease of access and collaboration offered by the cloud makes it particularly attractive for small and medium-sized enterprises that may not have the resources for on-premises solutions. As cloud technology continues to evolve, its integration with graph analytics is expected to drive significant market growth.

By Organization Size

Large Enterprises :

Large enterprises represent a significant segment of the graph analytics market, leveraging these solutions to handle massive volumes of complex data. Given their extensive operations and diverse datasets, large organizations are well-positioned to benefit from the insights generated by graph analytics. They utilize these tools for various applications, including customer segmentation, fraud detection, and supply chain optimization. The ability to analyze vast amounts of interconnected data enhances decision-making processes and allows for more effective risk management. Moreover, large enterprises often have the financial resources to invest in advanced graph analytics platforms, as well as the expertise to implement and maintain these systems successfully. The growing recognition of the value of data-driven insights across various functions within large organizations is expected to drive continued investment in graph analytics solutions.

Small and Medium-sized Enterprises :

Small and medium-sized enterprises (SMEs) are increasingly adopting graph analytics solutions, recognizing their potential to drive growth and improve competitiveness. With limited resources, SMEs often seek cost-effective cloud-based graph analytics solutions that can scale as their needs evolve. These tools help SMEs analyze customer behavior, optimize marketing strategies, and identify opportunities for improvement, all of which are crucial for sustainable growth. Additionally, the accessibility of advanced graph analytics capabilities through user-friendly interfaces allows SMEs without extensive data science expertise to leverage the power of data. As the emphasis on data-driven decision-making continues to rise, the graph analytics market is likely to witness significant uptake among SMEs looking to harness insights for strategic advantage.

By Application

Customer Analytics :

Customer analytics is one of the most critical applications of graph analytics, enabling organizations to understand and predict customer behavior. By analyzing the relationships between customers, their interactions, and preferences, businesses can develop personalized marketing strategies and enhance customer engagement. Graph analytics tools can help identify customer segments, track customer journeys, and analyze the impact of various touchpoints on purchasing decisions. This insight allows organizations to optimize their marketing efforts, improve customer retention, and drive sales growth. As competition intensifies across industries, the demand for effective customer analytics solutions is expected to rise, further propelling the graph analytics market.

Fraud Detection and Prevention :

Fraud detection and prevention is another vital application of graph analytics, particularly in sectors such as BFSI and e-commerce. By examining patterns in transactional data and identifying anomalies, organizations can uncover potential fraudulent activities before they escalate. Graph analytics enables the visualization of complex relationships and interactions, making it easier to spot suspicious behavior that may go unnoticed with traditional methods. The ability to analyze large volumes of data in real-time enhances the effectiveness of fraud detection, allowing organizations to respond promptly to threats. As fraud continues to evolve, the need for advanced analytics solutions is critical, driving growth in this segment of the market.

Risk Management and Compliance :

Risk management and compliance are increasingly reliant on graph analytics to navigate complex regulatory landscapes and assess potential risks. Organizations utilize graph analytics to model the relationships between various risk factors, enabling them to identify vulnerabilities and develop effective mitigation strategies. By visualizing risk data, businesses can communicate potential threats more clearly and make informed decisions to enhance compliance with regulatory requirements. As regulatory scrutiny intensifies across industries, the demand for robust risk management solutions powered by graph analytics is expected to grow substantially, shaping the future of this market segment.

Recommendation Engines :

Recommendation engines powered by graph analytics play a crucial role in enhancing user experiences across various platforms, including e-commerce, streaming services, and social media. By analyzing user interactions and preferences, organizations can generate personalized recommendations that drive engagement and increase conversions. Graph analytics allows for a deeper understanding of user behavior by considering the relationships between different users and items, leading to more accurate and relevant suggestions. As consumers increasingly expect tailored experiences, the demand for effective recommendation engines will continue to rise, further contributing to the overall growth of the graph analytics market.

Others :

In addition to the prominent applications mentioned, several other use cases are emerging within the graph analytics market, reflecting its versatility across diverse industries. Organizations leverage graph analytics for network analysis, supply chain optimization, social network analysis, and even healthcare diagnostics, where understanding relationships between various factors can lead to improved patient outcomes. As businesses seek to harness the full potential of their data, the exploration of innovative applications for graph analytics solutions is expected to broaden the market's scope. The increasing recognition of the value of graphed data in driving insights and operational efficiencies will contribute to the growth of this segment.

By Vertical

BFSI :

The BFSI (Banking, Financial Services, and Insurance) vertical is one of the largest adopters of graph analytics, utilizing the technology for various applications including fraud detection, risk assessment, and customer insights. Financial institutions face immense pressure to protect sensitive data and manage complex relationships between clients, transactions, and regulatory requirements. Graph analytics enables these organizations to identify suspicious activities by analyzing vast networks of transactions, thereby enhancing security measures. Furthermore, BFSI companies can leverage graph analytics to better understand customer behavior, improve service offerings, and optimize decision-making processes. As financial crimes become more sophisticated, the reliance on advanced analytics tools like graph analytics will continue to grow in this sector.

Retail and E-commerce :

Retail and e-commerce are rapidly adopting graph analytics to enhance customer experiences and streamline operations. By analyzing customer data, organizations can gain a comprehensive view of their customers’ preferences and behaviors, enabling them to tailor marketing strategies effectively. Graph analytics empowers retailers to optimize product recommendations, manage inventory efficiently, and improve supply chain logistics by visualizing complex relationships between products, suppliers, and customers. The insights generated through graph analytics contribute significantly to enhanced customer satisfaction and increased sales, making this vertical a critical driver of market growth. Retailers are increasingly recognizing the value of leveraging graphed data to inform strategic decisions and remain competitive in a dynamic market environment.

Healthcare and Life Sciences :

In the healthcare and life sciences sector, graph analytics is emerging as a powerful tool for improving patient outcomes and operational efficiency. By analyzing relationships between patients, treatments, and health outcomes, healthcare organizations can gain valuable insights that inform clinical decision-making and personalized medicine. Graph analytics helps in identifying disease patterns, tracking patient journeys, and optimizing resource allocation, which is vital in a sector that constantly evolves and faces regulatory challenges. Additionally, pharmaceutical companies can leverage graph analytics for drug discovery and development by visualizing complex biological relationships. As the healthcare landscape becomes increasingly complex, the demand for graph analytics solutions in this vertical will continue to rise, ultimately enhancing the quality of care provided to patients.

Telecom and IT :

The telecom and IT verticals are leveraging graph analytics to manage vast networks, optimize service delivery, and improve customer experiences. With the increase in connected devices and data traffic, telecom companies need advanced analytics tools to analyze network performance, detect anomalies, and optimize infrastructure. Graph analytics allows organizations to visualize and manage relationships among network components, identifying potential failures before they impact service quality. Furthermore, IT companies use graph analytics to enhance cybersecurity by analyzing user behavior patterns to detect potential threats. As the demand for reliable connectivity and data security grows, graph analytics will play an increasingly critical role in shaping the future of the telecom and IT sectors.

Others :

The "Others" category encompasses various industries that are beginning to recognize the value of graph analytics in driving business insights and efficiencies. Sectors such as transportation, energy, and manufacturing are exploring the applications of graph analytics for route optimization, resource management, and predictive maintenance. With the growing emphasis on operational efficiency and data-driven decision-making, more organizations across diverse verticals are likely to adopt graph analytics solutions to harness the power of their data. As the technology matures and becomes more accessible, its application across various industries will continue to expand, contributing to the overall growth of the market.

By Region

The regional analysis of the graph analytics market reveals distinct growth patterns across various geographical segments. North America holds a dominant position in the market, accounting for approximately 37% of the total market share in 2025. This growth is primarily driven by the presence of major technology players, a robust IT infrastructure, and a high adoption rate of advanced analytics solutions among enterprises. The United States and Canada are at the forefront of implementing innovative graph analytics applications, particularly in industries such as BFSI, healthcare, and retail. Furthermore, the region is expected to witness a CAGR of 29.0% during the forecast period, fueled by the increasing demand for data-driven insights and the continuous evolution of analytics technologies.

Europe follows closely behind, with a market share of around 30% in 2025. The growing focus on digital transformation and data-driven decision-making among European enterprises is driving the adoption of graph analytics solutions across various sectors, including telecommunications, finance, and manufacturing. Countries like Germany, the United Kingdom, and France are leading the charge in implementing graph analytics to optimize their operations and enhance customer experiences. Meanwhile, the Asia Pacific region is anticipated to experience the highest growth rate, with a CAGR of 32.5% during the forecast period. This rapid growth is attributed to the increasing volume of data generated by emerging markets, the rising adoption of cloud-based solutions, and the growing awareness of the importance of advanced analytics in driving business success.

Opportunities

The graph analytics market is poised for substantial opportunities as organizations increasingly recognize the need for advanced data analysis tools to navigate an ever-changing business landscape. One of the most significant opportunities lies in the rapid digital transformation occurring across various industries. As businesses transition to digital platforms, the volume of data generated is surging, creating an urgent demand for effective analytics solutions. Graph analytics is uniquely equipped to handle the complexities of this data, revealing insights that can drive strategic decision-making and operational efficiencies. Additionally, the proliferation of IoT devices is generating vast streams of interconnected data, which graph analytics can analyze to uncover valuable insights about user behavior and system performance. Organizations that invest in graph analytics will be well-positioned to capitalize on these trends and gain a competitive edge in their respective markets.

Moreover, as the focus on customer-centric approaches intensifies, organizations are increasingly turning to graph analytics for enhanced customer insights and personalization. The ability to analyze relationships and behaviors enables businesses to tailor their offerings and engage customers more effectively. This shift towards data-driven marketing and customer relationship management presents a lucrative opportunity for graph analytics providers to develop innovative solutions that address these evolving needs. Additionally, the rise of cloud-based solutions is making graph analytics more accessible to small and medium-sized enterprises, further widening the potential customer base. By leveraging these opportunities, graph analytics companies can drive growth and innovation in the market.

Threats

Despite the promising prospects for the graph analytics market, several threats could pose challenges to its growth trajectory. One significant threat is the increasing concern regarding data privacy and security. As organizations collect and analyze vast amounts of sensitive data, they face growing scrutiny from regulatory bodies and customers alike. Data breaches and misuse can lead to severe reputational damage, legal implications, and loss of customer trust. Companies must prioritize data governance and security measures to mitigate these risks, which may require additional investments and resources. Additionally, the competitive landscape of the data analytics market is becoming increasingly crowded, with numerous players vying for market share. This intense competition can lead to pricing pressures, potentially impacting profitability for graph analytics providers. Organizations must continuously innovate and differentiate their offerings to remain relevant in this evolving market.

Another critical threat comes from the rapid pace of technological advancements in the analytics space. As new technologies emerge, organizations may shift their focus toward alternative analytics solutions, potentially diminishing the demand for traditional graph analytics tools. Companies in the graph analytics market must stay ahead of the technological curve, adapting to changing customer preferences and evolving industry standards to maintain their competitive edge. Failure to do so could result in obsolescence in an environment that increasingly values agility and adaptability. This dynamic landscape requires ongoing monitoring and responsiveness to emerging trends to capitalize on opportunities while addressing potential threats.

Competitor Outlook

• Neo4j
• Oracle Corporation
• IBM Corporation
• Microsoft Corporation
• Amazon Web Services (AWS)
• DataStax
• TigerGraph
• SAS Institute Inc.
• ArangoDB
• QlikTech International AB
• Alteryx, Inc.
• RapidMiner, Inc.
• Informatica
• Graphistry
• Franz Inc.

The competitive landscape of the graph analytics market is characterized by the presence of several key players, each vying for a significant share through innovation, strategic partnerships, and comprehensive service offerings. Major companies like Neo4j and Oracle Corporation are leading the charge with robust graph database solutions that cater to diverse industry needs. Neo4j's platform is renowned for its flexibility and powerful query language, enabling businesses to conduct complex analyses with ease. Similarly, Oracle offers a suite of graph analytics tools that integrate seamlessly with its broader data management solutions, providing users with a comprehensive ecosystem for data analysis. The competitive edge of these companies stems from their ability to offer cutting-edge technologies combined with strong customer support and consulting services.

IBM Corporation and Microsoft Corporation are also key players in the market, leveraging their extensive expertise in analytics and cloud computing to enhance their graph analytics offerings. IBM's Watson and Microsoft Azure platforms provide organizations with powerful tools to process and analyze graph data efficiently. These companies continue to invest in research and development to incorporate AI and machine learning capabilities into their graph analytics solutions, thus enhancing predictive analytics and customer insights. Furthermore, Amazon Web Services (AWS) is making inroads into the market with its cloud-based graph database services, catering to organizations seeking scalable and flexible analytics solutions. The competitive landscape is continually evolving, with these major players driving innovation and shaping the future of graph analytics.

In addition to the established players, several emerging companies are making significant strides in the graph analytics space. DataStax and TigerGraph are gaining traction with their specialized graph databases that cater to the unique needs of specific industries. DataStax, for instance, positions itself as a leader in real-time analytics, while TigerGraph focuses on delivering high-performance and scalable graph analytics solutions. These companies are carving out niches within the market by addressing specific use cases and providing tailored solutions that resonate with their target audiences. As the demand for graph analytics continues to grow, the competitive landscape will likely witness the emergence of new players and innovative solutions that challenge the status quo and drive further advancements in the field.

• 1 Appendix

  • 1.1 List of Tables
  • 1.2 List of Figures

• 2 Introduction

  • 2.1 Market Definition
  • 2.2 Scope of the Report
  • 2.3 Study Assumptions
  • 2.4 Base Currency & Forecast Periods

• 3 Market Dynamics

  • 3.1 Market Growth Factors
  • 3.2 Economic & Global Events
  • 3.3 Innovation Trends
  • 3.4 Supply Chain Analysis

• 4 Consumer Behavior

  • 4.1 Market Trends
  • 4.2 Pricing Analysis
  • 4.3 Buyer Insights

• 5 Key Player Profiles

  • 5.1 Neo4j
    • 5.1.1 Business Overview
    • 5.1.2 Products & Services
    • 5.1.3 Financials
    • 5.1.4 Recent Developments
    • 5.1.5 SWOT Analysis
  • 5.2 ArangoDB
    • 5.2.1 Business Overview
    • 5.2.2 Products & Services
    • 5.2.3 Financials
    • 5.2.4 Recent Developments
    • 5.2.5 SWOT Analysis
  • 5.3 DataStax
    • 5.3.1 Business Overview
    • 5.3.2 Products & Services
    • 5.3.3 Financials
    • 5.3.4 Recent Developments
    • 5.3.5 SWOT Analysis
  • 5.4 Franz Inc.
    • 5.4.1 Business Overview
    • 5.4.2 Products & Services
    • 5.4.3 Financials
    • 5.4.4 Recent Developments
    • 5.4.5 SWOT Analysis
  • 5.5 Graphistry
    • 5.5.1 Business Overview
    • 5.5.2 Products & Services
    • 5.5.3 Financials
    • 5.5.4 Recent Developments
    • 5.5.5 SWOT Analysis
  • 5.6 TigerGraph
    • 5.6.1 Business Overview
    • 5.6.2 Products & Services
    • 5.6.3 Financials
    • 5.6.4 Recent Developments
    • 5.6.5 SWOT Analysis
  • 5.7 Informatica
    • 5.7.1 Business Overview
    • 5.7.2 Products & Services
    • 5.7.3 Financials
    • 5.7.4 Recent Developments
    • 5.7.5 SWOT Analysis
  • 5.8 Alteryx, Inc.
    • 5.8.1 Business Overview
    • 5.8.2 Products & Services
    • 5.8.3 Financials
    • 5.8.4 Recent Developments
    • 5.8.5 SWOT Analysis
  • 5.9 IBM Corporation
    • 5.9.1 Business Overview
    • 5.9.2 Products & Services
    • 5.9.3 Financials
    • 5.9.4 Recent Developments
    • 5.9.5 SWOT Analysis
  • 5.10 RapidMiner, Inc.
    • 5.10.1 Business Overview
    • 5.10.2 Products & Services
    • 5.10.3 Financials
    • 5.10.4 Recent Developments
    • 5.10.5 SWOT Analysis
  • 5.11 Oracle Corporation
    • 5.11.1 Business Overview
    • 5.11.2 Products & Services
    • 5.11.3 Financials
    • 5.11.4 Recent Developments
    • 5.11.5 SWOT Analysis
  • 5.12 SAS Institute Inc.
    • 5.12.1 Business Overview
    • 5.12.2 Products & Services
    • 5.12.3 Financials
    • 5.12.4 Recent Developments
    • 5.12.5 SWOT Analysis
  • 5.13 Microsoft Corporation
    • 5.13.1 Business Overview
    • 5.13.2 Products & Services
    • 5.13.3 Financials
    • 5.13.4 Recent Developments
    • 5.13.5 SWOT Analysis
  • 5.14 Amazon Web Services (AWS)
    • 5.14.1 Business Overview
    • 5.14.2 Products & Services
    • 5.14.3 Financials
    • 5.14.4 Recent Developments
    • 5.14.5 SWOT Analysis
  • 5.15 QlikTech International AB
    • 5.15.1 Business Overview
    • 5.15.2 Products & Services
    • 5.15.3 Financials
    • 5.15.4 Recent Developments
    • 5.15.5 SWOT Analysis

• 6 Market Segmentation

  • 6.1 Graph Analytics Market, By Component
    • 6.1.1 Software
    • 6.1.2 Services
  • 6.2 Graph Analytics Market, By Application
    • 6.2.1 Customer Analytics
    • 6.2.2 Fraud Detection and Prevention
    • 6.2.3 Risk Management and Compliance
    • 6.2.4 Recommendation Engines
    • 6.2.5 Others
  • 6.3 Graph Analytics Market, By Deployment Mode
    • 6.3.1 On-Premises
    • 6.3.2 Cloud
  • 6.4 Graph Analytics Market, By Organization Size
    • 6.4.1 Large Enterprises
    • 6.4.2 Small and Medium-sized Enterprises

• 7 Competitive Analysis

  • 7.1 Key Player Comparison
  • 7.2 Market Share Analysis
  • 7.3 Investment Trends
  • 7.4 SWOT Analysis

• 8 Research Methodology

  • 8.1 Analysis Design
  • 8.2 Research Phases
  • 8.3 Study Timeline

• 9 Future Market Outlook

  • 9.1 Growth Forecast
  • 9.2 Market Evolution

• 10 Geographical Overview

  • 10.1 Europe - Market Analysis
    • 10.1.1 By Country
      • 10.1.1.1 UK
      • 10.1.1.2 France
      • 10.1.1.3 Germany
      • 10.1.1.4 Spain
      • 10.1.1.5 Italy
  • 10.2 Asia Pacific - Market Analysis
    • 10.2.1 By Country
      • 10.2.1.1 India
      • 10.2.1.2 China
      • 10.2.1.3 Japan
      • 10.2.1.4 South Korea
  • 10.3 Latin America - Market Analysis
    • 10.3.1 By Country
      • 10.3.1.1 Brazil
      • 10.3.1.2 Argentina
      • 10.3.1.3 Mexico
  • 10.4 North America - Market Analysis
    • 10.4.1 By Country
      • 10.4.1.1 USA
      • 10.4.1.2 Canada
  • 10.5 Graph Analytics Market by Region
  • 10.6 Middle East & Africa - Market Analysis
    • 10.6.1 By Country
      • 10.6.1.1 Middle East
      • 10.6.1.2 Africa

• 11 Global Economic Factors

  • 11.1 Inflation Impact
  • 11.2 Trade Policies

• 12 Technology & Innovation

  • 12.1 Emerging Technologies
  • 12.2 AI & Digital Trends
  • 12.3 Patent Research

• 13 Investment & Market Growth

  • 13.1 Funding Trends
  • 13.2 Future Market Projections

• 14 Market Overview & Key Insights

  • 14.1 Executive Summary
  • 14.2 Key Trends
  • 14.3 Market Challenges
  • 14.4 Regulatory Landscape

Segments Analyzed in the Report

The global Graph Analytics market is categorized based on

By Component

• Software
• Services

By Deployment Mode

• On-Premises
• Cloud

By Organization Size

• Large Enterprises
• Small and Medium-sized Enterprises

By Application

• Customer Analytics
• Fraud Detection and Prevention
• Risk Management and Compliance
• Recommendation Engines
• Others

By Region

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa

Key Players

• Neo4j
• Oracle Corporation
• IBM Corporation
• Microsoft Corporation
• Amazon Web Services (AWS)
• DataStax
• TigerGraph
• SAS Institute Inc.
• ArangoDB
• QlikTech International AB
• Alteryx, Inc.
• RapidMiner, Inc.
• Informatica
• Graphistry
• Franz Inc.