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The market size for global graph database is expected to reach at USD 2 billion by 2025. Increasing demand for systems competencies of processing low latency queries, precise real-time data mining through visualization of results, along with adoption of AI-based graph database services and tools are responsible for the growth of graph database industry in the past few years. The requirement to detect intricate patterns at maximum scale is gaining traction. Moreover, the rapid adoption of virtualization for big data analytics is likely to provide lucrative prospects in the graph database industry. However, lack of programming ease and standardization are the factors to hinder the industry growth.
Graph databases comprises an online database management system in which the connected elements are associated together. Graph data enables to store data and correlate relationships between the data precisely compared to a relational database (RDBMS). Graph database is compatible with expanding data mode and appropriate for delivery in line with today’s varying delivery practices and business needs. Some of the key business giants implementing graph database are Google, Paypal, Facebook, and LinkedIn.
Key Segments of the Global Graph Database Market
Type Overview, 2018-2025 (USD Billion)
Application Overview, 2018-2025 (USD Billion)
Vertical Overview, 2018-2025 (USD Billion)
Regional Overview, 2018-2025 (USD Billion)
Reasons for the study
What does the report include?
Who should buy this report?
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.
The market size for global graph database is expected to reach at USD 2 billion by 2025. Increasing demand for systems competencies of processing low latency queries, precise real-time data mining through visualization of results, along with adoption of AI-based graph database services and tools are responsible for the growth of graph database industry in the past few years. The requirement to detect intricate patterns at maximum scale is gaining traction. Moreover, the rapid adoption of virtualization for big data analytics is likely to provide lucrative prospects in the graph database industry. However, lack of programming ease and standardization are the factors to hinder the industry growth.
Graph databases comprises an online database management system in which the connected elements are associated together. Graph data enables to store data and correlate relationships between the data precisely compared to a relational database (RDBMS). Graph database is compatible with expanding data mode and appropriate for delivery in line with today’s varying delivery practices and business needs. Some of the key business giants implementing graph database are Google, Paypal, Facebook, and LinkedIn.
Key Segments of the Global Graph Database Market
Type Overview, 2018-2025 (USD Billion)
Application Overview, 2018-2025 (USD Billion)
Vertical Overview, 2018-2025 (USD Billion)
Regional Overview, 2018-2025 (USD Billion)
Reasons for the study
What does the report include?
Who should buy this report?
Chapter 1 Introduction
1.1 Introduction to the Study
1.2 Market Definition and Scope
1.3 Units, Currency, Conversions and Years Considered
1.4 Key Stakeholders
1.5 Key Questions Answered
Chapter 2 Research Methodology
2.1 Introduction
2.2 Data Capture Sources
2.2.1 Primary Sources
2.2.2 Secondary Sources
2.3 Market Size Estimation
2.4 Market Forecast
2.5 Data Triangulation
2.6 Assumptions and Limitations
Chapter 3 Executive Summary
Chapter 4 Market Outlook
4.1 Introduction
4.2 Value Chain Analysis
4.3 Market Dynamics
4.3.1 Drivers
4.3.1.1 Growing Demand for Systems That Can Process Low-Latency Queries
4.3.1.2 Excellent Real-Time Big Data Mining With Visualization of Results to Drive the Market
4.3.2 Restraints
4.3.2.1 Lack of Standardization and Programming Ease
4.3.3 Opportunities
4.5 PEST Analysis
Chapter 5 Graph Database Market by Type
5.1 Introduction
5.1.1 RDF
5.1.2 Property Graph
Chapter 6 Graph Database Market by Application
6.1 Introduction
6.1.1 Customer Analytics
6.1.2 Risk & Compliance Management
6.1.3 Recommendation Engines
6.1.4 Fraud Detection
6.1.5 Supply Chain Management
6.1.6 Others
Chapter 7 Graph Database Market by Vertical
7.1 Introduction
7.1.1 Telecom & IT
7.1.2 BFSI
7.1.3 Retail
7.1.4 Government & Utilities
7.1.5 Media & Entertainment
7.1.6 Healthcare
7.1.7 Manufacturing
7.1.8 Others
Chapter 8 Graph Database Market By Region
8.1 Introduction
8.2 North America
8.2.1 U.S.
8.2.2 Canada
8.3 Europe
8.3.1 Germany
8.3.2 France
8.3.3 UK
8.3.4 Rest of Europe
8.4 Asia Pacific
8.4.1 China
8.4.2 Japan
8.4.3 India
8.4.4 Rest of Asia Pacific
8.5 Middle East & Africa
8.5.1 UAE
8.5.2 South Africa
8.5.3 Rest of Middle East & Africa
8.6 South America
8.6.1 Brazil
8.6.2 Rest of South America
Chapter 9 Competitive Landscape
9.1 Overview
9.2 Strategic Initiatives
9.2.1 Mergers & Acquisitions
9.2.2 New Product Launch
9.2.3 Investments
9.2.4 Expansion
9.2.5 Others
Chapter 10 Company Profiles
10.1 IBM
10.1.1 Overview
10.1.2 Products and Services Portfolio
10.1.3 Recent Initiatives
10.1.4 Company Financials
10.1.5 SWOT
10.2 Oracle
10.2.1 Overview
10.2.2 Products and Services Portfolio
10.2.3 Recent Initiatives
10.2.4 Company Financials
10.2.5 SWOT
10.3 AWS
10.3.1 Overview
10.3.2 Products and Services Portfolio
10.3.3 Recent Initiatives
10.3.4 Company Financials
10.3.5 SWOT
10.4 Microsoft
10.4.1 Overview
10.4.2 Products and Services Portfolio
10.4.3 Recent Initiatives
10.4.4 Company Financials
10.4.5 SWOT
10.5 Neo4j
10.5.1 Overview
10.5.2 Products and Services Portfolio
10.5.3 Recent Initiatives
10.5.4 Company Financials
10.5.5 SWOT
10.6 OrientDB
10.6.1 Overview
10.6.2 Products and Services Portfolio
10.6.3 Recent Initiatives
10.6.4 Company Financials
10.6.5 SWOT
10.7 Franz
10.7.1 Overview
10.7.2 Products and Services Portfolio
10.7.3 Recent Initiatives
10.7.4 Company Financials
10.7.5 SWOT
10.8 OpenLink Software
10.8.1 Overview
10.8.2 Products and Services Portfolio
10.8.3 Recent Initiatives
10.8.4 Company Financials
10.8.5 SWOT
10.9 TIBCO
10.9.1 Overview
10.9.2 Products and Services Portfolio
10.9.3 Recent Initiatives
10.9.4 Company Financials
10.9.5 SWOT
10.10 MarkLogic
10.10.1 Overview
10.10.2 Products and Services Portfolio
10.10.3 Recent Initiatives
10.10.4 Company Financials
10.10.5 SWOT
10.11 Other Companies