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How TigerGraph CoPilot enables graph-augmented AI
https://www.infoworld.com/article/3715344/how-tigergraph-copilot-enables-graph-augmented-ai.html?utm_source=dlvr.it&utm_medium=tumblr#tk.rss_machinelearning
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Graph Database Market set to hit USD 4.7 billion by 2030, with a 7.2% growth rate from 2023. Stay informed with the latest data on data management trends.
Graph Database Market Blog
Graph Database Market is Targeting USD 4.7 Billion by 2030
In 2023, the Graph Database Market reached a valuation of USD 2.9 billion. It is anticipated to achieve USD 4.7 billion by 2030, reflecting a steady growth rate of 7.2% during the forecast period from 2023 to 2030.
Introduction to Graph Database Market
The Graph Database Market is at the forefront of modern data management, offering organizations a powerful way to model, query, and analyze interconnected data relationships. Graph databases excel at capturing complex relationships between data points, making them ideal for applications ranging from social networks and recommendation engines to fraud detection and network analysis. In this blog, we delve into the Graph Database Market, uncovering its significance, key trends, and transformative impact on the world of data management.
Major Vendors in the Global Graph Database Market
Oracle Corporation
IBM Corporation
Amazon Web Services, Inc.
DataStax
Ontotext
Stardog Union
Hewlett Packard Enterprise
ArangoDB
Blazegraph
Microsoft Corporation
SAP SE
Teradata Corporation
Openlink Software
TIBCO Software, Inc.
Neo4j, Inc.
GraphBase
Cambridge Semantics
TigerGraph, Inc.
Objectivity Inc.
Bitnine Co, Ltd.
Franz Inc.
Redis Labs
Graph Story
Dgraph Labs
Eccenca
Fluree
Key Market Trends and Innovations
The Rise of Connected Data: In an increasingly interconnected world, traditional relational databases struggle to handle the complexity of relationships between data entities. Graph databases address this challenge by organizing data as nodes and edges, allowing for efficient traversal of interconnected data structures. This approach is particularly well-suited for applications requiring real-time insights into relationships, such as social networks, supply chain optimization, and knowledge graphs.
Knowledge Graphs and AI Applications: Graph databases serve as the backbone for building knowledge graphs, which are powerful tools for organizing and extracting insights from vast amounts of structured and unstructured data. By representing data as a graph of interconnected entities and attributes, knowledge graphs enable AI applications to reason, infer, and make context-aware decisions. Industries such as healthcare, e-commerce, and finance are leveraging knowledge graphs to power personalized recommendations, semantic search, and predictive analytics.
Real-Time Fraud Detection and Network Analysis: Graph databases are highly effective for detecting patterns of fraudulent behavior and uncovering hidden relationships in complex networks. By analyzing transactional data, social connections, and other sources of information, graph-based fraud detection systems can identify suspicious activities, uncover fraud rings, and prevent financial losses in real time. Similarly, graph-based network analysis tools are used in cybersecurity to detect and mitigate threats, analyze social networks, and optimize logistics and supply chain operations.
Hybrid and Multi-Model Graph Databases: As organizations seek more flexibility and scalability in managing diverse data types and workloads, hybrid and multi-model graph databases have emerged as popular solutions. These databases combine the strengths of graph data models with other data models, such as document, key-value, or columnar stores, allowing users to store and query data in the most suitable format for their use case. This flexibility enables organizations to leverage the benefits of graph databases while seamlessly integrating with existing data infrastructure.
Segmentations Analysis of Graph Database Market
By Component
Software
Services
By Type Of Database
Relational (SQL)
Non-Relational (No SQL)
By Analysis Type
Connectivity Analysis
Community Analysis
Centrality Analysis
By Deployment Mode
On Premise
Cloud Based
By Region
North America
US
Canada
Latin America
Brazil
Mexico
Argentina
Colombia
Chile
Peru
Rest of Latin America
Europe
UK
Germany
France
Italy
Spain
Russia
BENELUX
CIS & Russia
Nordics
Austria
Poland
Rest of Europe
Asia Pacific
China
Japan
India
South Korea
Thailand
Indonesia
Malaysia
Vietnam
Australia & New Zealand
Rest of Asia Pacific
Middle East & Africa
Saudi Arabia
UAE
South Africa
Nigeria
Egypt
Israel
Turkey
Rest of Middle East & Africa
Market Dynamics and Opportunities
The Graph Database Market is driven by several key dynamics and opportunities:
Growth in Data Complexity and Interconnectivity: With the proliferation of IoT devices, social media platforms, and interconnected systems, the volume and complexity of data continue to grow exponentially. Graph databases offer a scalable and efficient way to manage and analyze this interconnected data, providing organizations with actionable insights and competitive advantages in a data-driven world.
Demand for Real-Time Insights and Decision-Making: In today's fast-paced business environment, organizations require real-time insights to make informed decisions and respond quickly to changing market conditions. Graph databases enable real-time analysis of complex relationships and patterns, empowering businesses to detect emerging trends, optimize processes, and deliver personalized experiences to customers.
Adoption Across Diverse Industries: The versatility and applicability of graph databases span across various industries, including retail, healthcare, finance, telecommunications, and more. As organizations recognize the value of graph databases in driving innovation and unlocking new business opportunities, adoption is expected to continue growing across verticals, fueling market expansion and innovation.
Conclusion
The Graph Database Market is poised for continued growth and innovation as organizations increasingly rely on interconnected data to drive business success. With their ability to model complex relationships, uncover hidden insights, and deliver real-time analytics, graph databases are reshaping the way organizations manage and derive value from their data assets. As the demand for scalable, flexible, and high-performance data management solutions continues to rise, the Graph Database Market will remain a key enabler of digital transformation and innovation in the years to come.
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Source: https://www.whatech.com/og/markets-research/it/809311-graph-database-market-is-targeting-usd-4-7-billion-by-2030&sa=U&ved=2ahUKEwjsy8OM0s-FAxWjGFkFHbmWBzQQxfQBegQIBBAC&usg=AOvVaw2PITmMPUr2Lc1o8lvj_AWm
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Represent your inner strength with this white Siberian tiger shirt! This shirt reads “I’ve got the eye of a tiger”. A great gift for any tiger or cat lover!! Link to shop in bio! #tigerlovers #whitetiger #eyeofthetiger #tigerart #clothing #unisexshirt #etsy #etsyshops #blossomingmindink #tigergifts #siberiantiger #siberiantigergifts #whitetiger #bigcat #tigergraphic #natureshirt #animalart #tigerseye #bluetigereye #gift #fathersdaygift #whitesiberian #forestanimal #asiantiger #innerstrength https://www.instagram.com/p/ByqMNehntnu/?igshid=1fdjh4zjk6q1j
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Graph databases are surely the future. But what are they? You can check out this blogpost to get a gentle introduction to graphs and graph databases.
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บทความ TigerGraph มิติใหม่ของการวิเคราะห์ข้อมูลรูปแบบของกราฟ ที่องค์กรใหญ่ต้องมี โดย iyeanzii เผยแพร่ May 23, 2022 at 05:18PM via DigitalMore
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TigerGraph มิติใหม่ของการวิเคราะห์ข้อมูลรูปแบบของกราฟ ที่องค์กรใหญ่ต้องมี
ไม่ว่าจะเป็นองค์กรหรือธุรกิจแบบไหน การเลือกใช้เครื่องมือในการจัดการข้อมูลที่ดี ย่อมส่งผลให้องค์กรสามารถวิเคราะห์ข้อมูลได้อย่างมีประสิทธิภาพมากยิ่งขึ้น และสามารถนำไปใช้ในการตัดสินใจเชิง กลยุทธ์ได้อย่างแม่นยำ โดยเครื่องมือในการจัดการข้อมูล หรือ Data Analytics Tools นั้นมีมากมายหลายรูปแบบ ไม่ว่าจะเป็นการใช้ Excel, BI Tools, หรือแม้แต่การเขียนโปรแกรมด้วยภาษา R หรือ Python source https://digitalmore.co/tigergraph-stelligence/
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บทความ Stelligence จัดสัมมนาปลดล็อกสกิล Data Science เสริมสร้างด้วยเทคโนโลยี Tigergraph โดย Mayy Kornanong เผยแพร่ May 14, 2022 at 03:48PM via DigitalMore
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Stelligence จัดสัมมนาปลดล็อกสกิล Data Science เสริมสร้างด้วยเทคโนโลยี Tigergraph
STelligence เปิดเกมรุกเสริมสร้างศักยภาพด้านการวิเคราะห์ข้อมูล จัดสัมมนาออนไลน์ในหัวข้อ Unlock your analytics potential and grow 10x with the new graph technology ด้วย Tigergraph เทคโนโลยีกราฟทรงพลัง เครื่องมือที่ช่วยปลดล็อกศักยภาพในการวิเคราะห์และกระตุ้นการเติบโต 10 เท่า ในวันที่ 20 พฤษภาคม 2565 เวลา 14.00-15.30 น. source https://digitalmore.co/stelligence-data-science-tigergraph/
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