The main stock market index of United States, the US500, rose to 6762 points on October 24, 2025, gaining 0.35% from the previous session. Over the past month, the index has climbed 2.38% and is up 16.42% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on October of 2025.

The global graph database market size reached USD 2.0 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 8.6 Billion by 2033, exhibiting a growth rate (CAGR) of 17.57% during 2025-2033. The increasing adoption of graph databases in cybersecurity for threat detection and network analysis, growing demand for real-time analytics and AI-driven insights, and expanding application in industries, such as healthcare and finance, for data integration and personalized services, are some of the key factors catalyzing the market growth.

IMARC Group provides an analysis of the key trends in each segment of the global graph database market report, along with forecasts at the global, regional, and country levels from 2025-2033. Our report has categorized the market based on component, type of database, analysis type, deployment model, application, and industry vertical.

The main stock market index of United States, the US500, rose to 6792 points on October 24, 2025, gaining 0.79% from the previous session. Over the past month, the index has climbed 2.83% and is up 16.93% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on October of 2025.

The global Graph Database market size reached USD 1.59 Billion in 2020 and revenue is forecasted to reach USD 11.25 Billion in 2030 registering a CAGR of 21.9%. Graph Database (GDB) industry report classifies global market by share, trend, growth and on the basis of component, deployment, graph type...

Graph Database Market size was valued at USD 2.86 Billion in 2024 and is projected to reach USD 14.58 Billion by 2032, growing at a CAGR of 22.6% from 2026 to 2032. Global Graph Database Market DriversThe growth and development of the Graph Database Market is attributed to certain main market drivers. These factors have a big impact on how Graph Database are demanded and adopted in different sectors. Several of the major market forces are as follows:Growth of Connected Data: Graph databases are excellent at expressing and querying relationships as businesses work with datasets that are more complex and interconnected. Graph databases are becoming more and more in demand as connected data gains significance across multiple industries.Knowledge Graph Emergence: In fields like artificial intelligence, machine learning, and data analytics, knowledge graphs—which arrange information in a graph structure—are becoming more and more popular. Knowledge graphs can only be created and queried via graph databases, which is what is causing their widespread use.Analytics and Machine Learning Advancements: Graph databases handle relationships and patterns in data effectively, enabling applications related to advanced analytics and machine learning. Graph databases are becoming more and more in demand when combined with analytics and machine learning as businesses want to extract more insights from their data.Real-Time Data Processing: Graph databases can process data in real-time, which makes them appropriate for applications that need quick answers and insights. In situations like fraud detection, recommendation systems, and network analysis, this is especially helpful.Increasing Need for Security and Fraud Detection: Graph databases are useful for fraud security and detection applications because they can identify patterns and abnormalities in linked data. The growing need for graph databases in security solutions is a result of the ongoing evolution of cybersecurity threats.

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about stock market, New York, indexes, and USA.

United States graph database market size reached USD 537.9 Million in 2024. Looking forward, IMARC Group expects the market to reach USD 2,754.7 Million by 2033, exhibiting a growth rate (CAGR) of 19.7% during 2025-2033​. The widespread adoption of this innovative approach, as it offers numerous advantages over traditional database solutions in terms of computing power, storage, indexing, querying, etc., is primarily driving the market growth across the country.

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for ​2025-2033​. Our report has categorized the market based on component, type of database, analysis type, deployment model, application, and industry vertical.

The Global Graph Database Market, valued at USD 3.12 billion in 2024, is projected to grow at a 23.56% CAGR from 2025-30, driven by AI tools and low-latency query processing.

Knowledge Graph Market size was valued at USD 7.19 Billion in 2024 and is expected to reach USD 4.1 Billion by 2032, growing at a CAGR of 18.1% from 2025 to 2032.

Knowledge Graph Market Drivers

Enhanced Data Integration and Analysis: Knowledge graphs excel at integrating and analyzing data from diverse sources, including structured, semi-structured, and unstructured data. This enables organizations to gain a holistic view of information and make more informed decisions. Improved Search and Information Retrieval: Knowledge graphs provide a more semantic understanding of information, enabling more accurate and relevant search results. Instead of just keyword matching, knowledge graphs understand the relationships between entities and provide more contextually relevant information. Personalized Experiences: Knowledge graphs can be used to personalize user experiences by understanding individual preferences, interests, and behaviors. This is crucial for applications like personalized recommendations, targeted advertising, and customer service. AI and Machine Learning: Knowledge graphs are essential for powering AI and machine learning applications, such as chatbots, recommendation systems, and fraud detection. They provide a structured representation of knowledge that AI/ML models can easily understand and utilize. Business Intelligence and Decision Making: Knowledge graphs can help businesses gain deeper insights into their customers, markets, and operations. They can be used to identify trends, predict future outcomes, and make more informed business decisions.

India's main stock market index, the SENSEX, fell to 84212 points on October 24, 2025, losing 0.41% from the previous session. Over the past month, the index has climbed 3.76% and is up 6.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on October of 2025.

Global Graph Technology Market Share size and share are expected to exceed USD 23.48 billion by 2032, with a compound annual growth rate (CAGR) of 21.9% during the forecast period.

In 2023, the Graph Technologies Market was valued at $3.44 Bn, and projected to reach $13.26 Bn by 2030 due to the expansion of connected devices globally

Identity Graph AI Market Outlook

According to our latest research, the global Identity Graph AI market size reached USD 2.4 billion in 2024, demonstrating robust momentum driven by increasing digital transformation and stringent data privacy regulations. The market is projected to grow at a CAGR of 18.6% from 2025 to 2033, reaching an estimated USD 12.4 billion by 2033. This impressive growth trajectory is primarily fueled by the rising adoption of AI-driven identity resolution solutions across industries seeking to enhance customer engagement, mitigate fraud, and ensure regulatory compliance.

The rapid proliferation of digital channels and the exponential growth in consumer data have become pivotal growth factors for the Identity Graph AI market. Enterprises are increasingly leveraging AI-powered identity graphs to unify disparate data points and create comprehensive, real-time customer profiles. This unified view enables businesses to deliver hyper-personalized experiences, optimize marketing efforts, and foster deeper customer loyalty. The surge in omnichannel marketing strategies, coupled with the need to address data silos, is compelling organizations to invest in advanced identity resolution technologies, thereby accelerating market expansion.

Another significant driver is the escalating threat landscape associated with digital fraud and identity theft. As cybercriminals deploy sophisticated tactics, organizations are under immense pressure to safeguard sensitive customer information and ensure secure transactions. Identity Graph AI solutions, with their ability to detect anomalies, flag suspicious activities, and authenticate user identities across touchpoints, are emerging as critical tools in the fight against fraud. The integration of machine learning and advanced analytics into identity graphs further enhances their predictive capabilities, empowering organizations to proactively address security risks and comply with evolving regulatory mandates such as GDPR and CCPA.

The evolving regulatory environment is also catalyzing the adoption of Identity Graph AI solutions. With governments worldwide enacting stringent data privacy laws, organizations are compelled to implement robust identity management frameworks that guarantee data accuracy, transparency, and consent management. AI-powered identity graphs play a crucial role in helping businesses align with these regulations by providing a centralized and auditable record of customer identities and interactions. This not only mitigates compliance risks but also builds consumer trust, which is increasingly recognized as a competitive differentiator in the digital economy.

Regionally, North America continues to dominate the Identity Graph AI market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. North America’s leadership is attributed to its mature digital infrastructure, high adoption of AI technologies, and proactive regulatory stance on data privacy. Meanwhile, the Asia Pacific region is witnessing the fastest growth, spurred by rapid digitalization, expanding e-commerce ecosystems, and increasing investments in AI-driven security solutions. Europe’s growth is reinforced by stringent data protection regulations and a strong emphasis on customer-centric digital transformation initiatives.

Component Analysis

The Identity Graph AI market is segmented by component into Software and Services, each playing a distinct role in shaping the overall market landscape. Software solutions form the backbone of the market, encompassing advanced platforms that leverage AI and machine learning algorithms to aggregate, match, and resolve identity data from multiple sources. These platforms are designed to deliver real-time, unified customer views, enabling organizations to drive targeted marketing, enhance customer experiences, and bolster security measures. The growing demand for sophisticated identity resolution capabilities is propelling continuous innovation in software offerings, with vendors introducing features such as automated data cleansing, graph-based analytics, and privacy-centric design.

Services, comprising consulting, integration, and support, are integral to the successful deployment and adoption of Identity Graph AI solutions. As organizations grapple with complex data environments and evolving regulatory requirements, the need for expert guidance and cus

According to Cognitive Market Research, the global Graph Analytics market size was USD 2522 million in 2024 and will expand at a compound annual growth rate (CAGR) of 34.0% from 2024 to 2031. Key Dynamics of Graph Analytics Market

Key Drivers of Graph Analytics Market

Increasing Demand for Immediate Big Data Insights: Organizations are progressively depending on graph analytics to handle extensive amounts of interconnected data for instantaneous insights. This is essential for applications such as fraud detection, recommendation systems, and customer behavior analysis, particularly within the finance, retail, and social media industries.

Rising Utilization in Fraud Detection and Cybersecurity: Graph analytics facilitates the discovery of intricate relationships within transactional data, aiding in the identification of anomalies, insider threats, and fraudulent patterns. Its capacity to analyze nodes and edges in real-time is leading to significant adoption in cybersecurity and banking sectors.

Progress in AI and Machine Learning Integration: Graph analytics platforms are progressively merging with AI and ML algorithms to improve predictive functionalities. This collaboration fosters enhanced pattern recognition, network analysis, and more precise forecasting across various sectors including healthcare, logistics, and telecommunications.

Key Restrains for Graph Analytics Market

High Implementation and Infrastructure Expenses: Establishing a graph analytics system necessitates sophisticated infrastructure, storage, and processing capabilities. These substantial expenses may discourage small and medium-sized enterprises from embracing graph-based solutions, particularly in the absence of a clear return on investment.

Challenges in Data Modeling and Querying: In contrast to conventional relational databases, graph databases demand specialized expertise for schema design, data modeling, and query languages such as Cypher or Gremlin. This significant learning curve hampers adoption in organizations lacking technical expertise.

Concerns Regarding Data Privacy and Security: Since graph analytics frequently involves the examination of sensitive personal and behavioral data, it presents regulatory and privacy challenges. Complying with data protection regulations like GDPR becomes increasingly difficult when handling large-scale, interconnected datasets.

Key Trends in Graph Analytics Market

Increased Utilization in Supply Chain and Logistics Optimization: Graph analytics is increasingly being adopted in logistics for the purpose of mapping routes, managing supplier relationships, and pinpointing bottlenecks. The implementation of real-time graph-based decision-making is enhancing both efficiency and resilience within global supply chains.

Growth of Cloud-Based Graph Analytics Platforms: Cloud service providers such as AWS, Azure, and Google Cloud are broadening their support for graph databases and analytics solutions. This shift minimizes initial infrastructure expenses and facilitates scalable deployments for enterprises of various sizes.

Advent of Explainable AI (XAI) in Graph Analytics: The need for explainability is becoming a significant priority in graph analytics. Organizations are pursuing transparency regarding how graph algorithms reach their conclusions, particularly in regulated sectors, which is increasing the demand for tools that offer inherent interpretability and traceability. Introduction of the Graph Analytics Market

The Graph Analytics Market is rapidly expanding, driven by the growing need for advanced data analysis techniques in various sectors. Graph analytics leverages graph structures to represent and analyze relationships and dependencies, providing deeper insights than traditional data analysis methods. Key factors propelling this market include the rise of big data, the increasing adoption of artificial intelligence and machine learning, and the demand for real-time data processing. Industries such as finance, healthcare, telecommunications, and retail are major contributors, utilizing graph analytics for fraud detection, personalized recommendations, network optimization, and more. Leading vendors are continually innovating to offer scalable, efficient solutions, incorporating advanced features like graph databases and visualization tools.

The Knowledge Graph Technology market is experiencing robust growth, driven by the increasing need for enhanced data organization, improved search capabilities, and the rise of artificial intelligence (AI) and machine learning (ML) applications. The market's expansion is fueled by several key factors, including the growing volume of unstructured data, the need for better data integration across disparate sources, and the demand for more intelligent and context-aware applications. Businesses across various sectors, including healthcare, finance, and e-commerce, are adopting knowledge graphs to enhance decision-making, improve customer experiences, and gain a competitive advantage. The market is witnessing significant advancements in graph database technologies, semantic technologies, and knowledge representation techniques, further accelerating its growth trajectory. While challenges such as data quality issues and the complexity of implementing and maintaining knowledge graphs exist, the substantial benefits are driving widespread adoption. We project a substantial increase in market size over the next decade, with particular growth anticipated in regions with advanced digital infrastructures and strong investments in AI and data analytics. The segmentation of the market by application (e.g., customer relationship management, fraud detection, supply chain optimization) and type (e.g., ontology-based, rule-based) reflects the diverse use cases driving adoption across different sectors. The forecast for Knowledge Graph Technology demonstrates continued, albeit potentially moderating, growth through 2033. While the initial years will likely see strong expansion driven by early adoption and technological advancements, the growth rate might stabilize as the market matures. However, continued innovation, particularly in areas like integrating knowledge graphs with emerging technologies such as the metaverse and Web3, and expansion into new applications within industries like personalized medicine and smart manufacturing, will ensure sustained, though potentially less rapid, growth. Geographical expansion, particularly into developing economies with increasing digitalization, presents a significant opportunity for market expansion. Competitive pressures among vendors will drive further innovation and potentially lead to consolidation within the market. Therefore, a thorough understanding of market segmentation, competitive dynamics, and technological advancements is crucial for stakeholders to navigate the evolving landscape and capitalize on emerging opportunities.

In 2024, Market Research Intellect valued the Knowledge Graph Market Report at USD 4.5 billion, with expectations to reach USD 12.1 billion by 2033 at a CAGR of 15.0%.Understand drivers of market demand, strategic innovations, and the role of top competitors.

Graph and download economic data for Stock Market Total Value Traded to GDP for United States (DDDM02USA156NWDB) from 1975 to 2019 about market cap, stock market, trade, GDP, and USA.

Hong Kong's main stock market index, the HK50, rose to 26160 points on October 24, 2025, gaining 0.74% from the previous session. Over the past month, the index has declined 1.23%, though it remains 27.05% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on October of 2025.

According to Cognitive Market Research, the global Graph Database market size was USD 7.3 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 20.2% from 2024 to 2031. Market Dynamics of Graph Database Market

Key Drivers for Graph Database Market

Increasing demand for solutions with the capability to process low-latency queries-One of the main reasons the Graph Database market is extensively being used all over the globe, to the extent that numerous legacy database providers are endeavoring to assimilate graph database schemas into their main relational database infrastructures. Whereas, in theory, the strategy might save money, it might degrade and slow down the performance of queries run beside the database. A graph database is altering traditional brick-and-mortar trades into digital business powerhouses in terms of digital business activities.
Growing usage of graph database technology to drive the Graph Database market's expansion in the years ahead.

Key Restraints for Graph Database Market

Complex programming and standardization pose a serious threat to the Graph Database industry.
The market also faces significant difficulties related to low-cost clusters.

Introduction of the Graph Database Market

The graph database market has experienced significant growth due to the increasing need for efficient data management and complex relationship mapping in various industries. Unlike traditional relational databases, graph databases excel in handling interconnected data, making them ideal for applications such as social networks, fraud detection, recommendation engines, and supply chain management. Key drivers of this market include the rising adoption of big data analytics, advancements in artificial intelligence, and the proliferation of connected devices. Leading players, such as Neo4j, Amazon Web Services, and Microsoft, continue to innovate, offering scalable and robust graph database solutions. The growing demand for real-time, low-latency data processing capabilities further propels the market's expansion.

Get key insights on Market Research Intellect's Graph Analytics Market Report: valued at USD 3.2 billion in 2024, set to grow steadily to USD 10.5 billion by 2033, recording a CAGR of 14.5%.Examine opportunities driven by end-user demand, R&D progress, and competitive strategies.