The Graph Database Market size was valued at US$ 2.25 billion in 2022 and is expected to reach US$ 11.55 billion in 2030 with a growing CAGR of 22.7% over the forecast period 2023-2030.
Graph database represent a class of transactional technologies designed specifically for online transaction processing (OLTP) databases. The market for these databases is poised for significant growth, driven by the rising adoption of AI-based graph database services and tools. Additionally, the increasing demand for solutions capable of processing low-latency queries further contributes to this upward trend. Moreover, the urgent need to identify complex patterns and virtualize big data analytics is expected to play a pivotal role in propelling the graph database market forward in the near future.
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Market Definition
A graph database is a particular kind of database that uses graph topologies for semantic searches and stores and represents data as nodes, edges, and properties. Each node represents an object between two nodes, and each edge represents a link or relationship between them. The technologies that convert relational online transaction processing (OLTP) databases into graph databases are called graph databases.
Drivers
Increased use of connected data to improve marketing results
Increase in Adoption of Graph Database Software in the Healthcare Sector
Graph database software plays a crucial role in the healthcare and life sciences sectors by efficiently recording and disseminating patient information. This technology is revolutionizing the way healthcare providers and patients access and share vital data. In fact, innovative start-ups in the healthcare industry are capitalizing on the power of graph database software to meet the unmet needs of their customers. One such example is Zephyr Health, a health-focused start-up that has successfully integrated graph database technology into its service offerings.
Furthermore, established healthcare organizations and institutions are embracing graph database tools to optimize their operations, enhance safety measures, reduce costs, and elevate the quality of patient care. This widespread adoption of graph database software is a testament to its effectiveness and potential to revolutionize the healthcare sector.
By leveraging graph database technology, healthcare providers can streamline their processes, ensuring that patient information is readily available to those who need it. This not only improves operational efficiency but also enhances patient safety and care. Additionally, the utilization of graph database software enables healthcare organizations to identify patterns and trends in patient data, leading to more accurate diagnoses and personalized treatment plans.
Moreover, the implementation of graph database software in the healthcare sector has proven to be cost-effective. By eliminating the need for multiple systems and databases, healthcare organizations can significantly reduce their expenses while improving data management and accessibility.
Restrains
The absence of standards and simple programming
Although theoretically NoSQL databases and graph databases must be run on a single machine because they cannot be implemented across a low-cost cluster. This is the cause of the network's rapid performance decline. Another potential drawback is that since there is no Standard Query Language (SQL) to retrieve data from graph databases, developers must write their queries in Java. This requires hiring expensive programmers, or they must use SparcQL or another query language designed to support graph databases, which would require learning a new skill. Because of this, graph database systems lack programming simplicity and standardization. Although there are graph database visualization tools on the market, they are still in the early stages of development.
Opportunities
Growing use of graph database tools and services powered by artificial intelligence (AI).
There is an increasing need for low-latency query processing systems.
Open knowledge networks' emergence
Challenges
Insufficient technical expertise is a common challenge faced by individuals or organizations.
If companies that produce graph database software or hardware components have operations or suppliers in Ukraine or Russia, disruptions in the supply chain due to the conflict could lead to delays in product development or manufacturing.
The war can affect exchange rates and currency values, which, in turn, can impact the cost of technology imports and exports. Companies that rely on foreign markets for graph database sales could face challenges if exchange rates become volatile by 10%. The conflict might prompt organizations to reevaluate their data privacy and security measures. Graph databases are often used to analyze and manage sensitive data. An escalation in cyberattacks or concerns about data security could lead to an increased 6% demand for graph database solutions. Governments may impose new regulations or sanctions in response to the conflict. This could affect international trade and business operations, potentially impacting companies in the graph database market. The Russia-Ukraine war can change the priorities of industries and governments. For example, increased focus on national security might lead to higher demand for graph database solutions in defense and intelligence sectors. If the conflict escalates and disrupts global trade, it could have broader economic repercussions. A global economic downturn could reduce overall IT spending, which might affect the graph database market.
Impact of Recession
In times of economic uncertainty, businesses tend to prioritize cost efficiency and cost reduction 7.2% in many organizations. Graph databases, while powerful for certain use cases, can be perceived as more complex and potentially costly to implement and maintain compared to traditional relational databases. This might lead to a preference for more established and cost-effective database solutions. Graph databases are particularly suited for applications that involve complex relationships and interconnected data, such as social networks, fraud detection, and recommendation systems. During a recession, some of these use cases might see reduced activity, while others, like fraud detection, might become more critical. The net impact on the market will depend on the mix of use cases.
On the flip side, recessions can also spur innovation as companies seek more efficient and effective solutions to address their business challenges. Some organizations may turn to graph databases to gain a competitive advantage by better understanding their data and relationships within it. Companies that were considering adopting graph databases before a recession might delay their plans due to economic uncertainty. However, once economic conditions stabilize, they could resume or accelerate their adoption of these technologies, potentially leading to a rebound in the market.
By Component
Software
Services
By Deployment
Cloud
On-Premise
By Type
Relational (SQL)
Non-Relational (NoSQL)
By Application
Identity and Access Management
Customer Analytics
Recommendation Engine
Master Data Management
Privacy and Risk Compliance
Fraud Detection and Risk Management
Others
By Analysis Type
Community Analysis
Connectivity Analysis
Centrality Analysis
Path Analysis
By End User
Banking, Financial Services and Insurance (BFSI)
IT & Telecommunication
Retail
Healthcare
Life Science
Media & Entertainment
Government
Others
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Due to the emergence of technology-based industries and businesses, graph database players in the region are expected to experience significant market growth. North America accounts for 39.2% of the global Revenue of the market. As most enterprises rely on data, this is driving the adoption of graph database services & and tools and related technologies. Additionally, vendor investments are boosting the market's expansion. For instance, California-based TigerGraph raised USD 33 million for graph database products.
Due to the development of IoT devices, industrial companies, and the emergence of artificial intelligence-based graph database providers, Asia Pacific is also anticipated to experience considerable growth in the graph database industry. Additionally, several Asian nations are using information-intensive technology to gain an advantage over rivals. These elements are more likely to produce opportunities for vendors of graph databases and fuel market expansion in the area. Due to the growing demand for improved data visualization tools, the Middle East and Africa are more likely to experience growth. In addition, a number of regional government initiatives are anticipated to fuel market expansion.
REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
The major players in market are Oracle Corporation, Ontotext, Orient DB, Hewlett Packard Enterprise, Microsoft Corporation, Teradata Corporation, Stardog Union Inc., Amazon Web Services, Inc., Objectivity Inc., MangoDB, TIBCO Software, Franz Inc., TigerGraph Inc., DataStax, IBM Corporation, Blazegraph, Openlink Software, MarkLogic Corporation, GraphBase, Neon4j Inc., ArangoDB, and others in final report.
MarkLogic Corporation released MarkLogic Data Hub Central in April 2021 with a no-code or low-code user interface. Through the introduction of MarkLogic, businesses now have a clear roadmap for modernizing their data infrastructure for the cloud.
The graph database from the firm, NEO4J version 4.3, was launched in June 2021. It includes minor upgrades that highlight earlier inventions. The most recent version boosts performance with new intelligent IO scheduling, relationship and relationship property indexes, faster write transaction throughput, graph data science, and parallelized backup.
A data lineage platform called MANTA established a strategic agreement with Neo4j in April 2021 to directly include Neo4j's graph database technology into MANTA's platform for pipeline analysis. As businesses continue their digital transformation, customers will be able to quickly process ever-larger volumes of data thanks to better graph database capabilities.
| Report Attributes | Details |
| Market Size in 2022 | US$ 2.25 Bn |
| Market Size by 2030 | US$ 11.55 Bn |
| CAGR | CAGR of 22.77 % From 2023 to 2030 |
| Base Year | 2022 |
| Forecast Period | 2023-2030 |
| Historical Data | 2019-2021 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Component (Software, Services) • By Deployment (Cloud, On-Premise) • By Type (Relational (SQL), Non-Relational (NoSQL)) • By Application (Identity and Access Management, Customer Analytics, Recommendation Engine, Master Data Management, Privacy and Risk Compliance, Fraud Detection and Risk Management, Others) • By Analysis Type (Community Analysis, Connectivity Analysis, Centrality Analysis, Path Analysis) • By End User (Banking, Financial Services and Insurance (BFSI), IT & Telecommunication, Retail, Healthcare, Life Science, Media & Entertainment, Government, Others), |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Company Profiles | Oracle Corporation, Ontotext, Orient DB, Hewlett Packard Enterprise, Microsoft Corporation, Teradata Corporation, Stardog Union Inc., Amazon Web Services, Inc., Objectivity Inc., MangoDB, TIBCO Software, Franz Inc., TigerGraph Inc., DataStax, IBM Corporation, Blazegraph, Openlink Software, MarkLogic Corporation, GraphBase, Neon4j Inc., ArangoDB |
| Key Drivers | • Increased use of connected data to improve marketing results • Increase in Adoption of Graph Database Software in the Healthcare Sector |
| Market Restraints | • The absence of standards and simple programming |
Ans: The market is expected to grow to USD 11.55 billion by the forecast period of 2030.
Ans. The CAGR of the Graph Database Market for the forecast period 2022-2030 is 22.7 %.
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Ans: North American region is dominating the Graph Database Market
Ans. The major players in the market are Oracle Corporation, Ontotext, Orient DB, Hewlett Packard Enterprise, Microsoft Corporation, Teradata Corporation, Stardog Union Inc., Amazon Web Services, Inc., Objectivity Inc., MangoDB, DataStax, IBM Corporation, Blazegraph, Openlink Software, MarkLogic Corporation, GraphBase, Neon4j Inc., ArangoDB, and others in final report.
Table of Contents
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges
4. Impact Analysis
4.1 Impact of Russia-Ukraine War
4.2 Impact of Ongoing Recession
4.2.1 Introduction
4.2.2 Impact on major economies
4.2.2.1 US
4.2.2.2 Canada
4.2.2.3 Germany
4.2.2.4 France
4.2.2.5 United Kingdom
4.2.2.6 China
4.2.2.7 japan
4.2.2.8 South Korea
4.2.2.9 Rest of the World
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Graph Database Market Segmentation, By Component
8.1 Software
8.2 Services
9. Graph Database Market Segmentation, By Deployment
9.1 Cloud
9.2 On-Premise
10. Graph Database Market Segmentation, By Type
10.1 Relational (SQL)
10.2 Non-Relational (NoSQL)
11. Graph Database Market Segmentation, By Application
11.1 Identity and Access Management
11.2 Customer Analytics
11.3 Recommendation Engine
11.4 Master Data Management
11.5 Privacy and Risk Compliance
11.6 Fraud Detection and Risk Management
11.7 Others
12. Graph Database Market Segmentation, By Analysis Type
12.1 Community Analysis
12.2 Connectivity Analysis
12.3 Centrality Analysis
12.4 Path Analysis
13. Graph Database Market Segmentation, By End User
13.1 Banking, Financial Services and Insurance (BFSI)
13.2 IT & Telecommunication
13.3 Retail
13.4 Healthcare
13.5 Life Science
13.6 Media & Entertainment
13.7 Government
13.8 Others
14. Regional Analysis
14.1 Introduction
14.2 North America
14.2.1 North America Graph Database Market By Country
14.2.2 North America Graph Database Market By Component
14.2.3 North America Graph Database Market By Deployment
14.2.4 North America Graph Database Market By Type
14.2.5 North America Graph Database Market By Application
14.2.6 North America Graph Database Market By Analysis Type
14.2.7 North America Graph Database Market By End User
14.2.8 USA
14.2.8.1 USA Graph Database Market By Component
14.2.8.2 USA Graph Database Market By Deployment
14.2.8.3 USA Graph Database Market By Type
14.2.8.4 USA Graph Database Market By Application
14.2.8.5 USA Graph Database Market By Analysis Type
14.2.8.6 USA Graph Database Market By End User
14.2.9 Canada
14.2.9.1 Canada Graph Database Market By Component
14.2.9.2 Canada Graph Database Market By Deployment
14.2.9.3 Canada Graph Database Market By Type
14.2.9.4 Canada Graph Database Market By Application
14.2.9.5 Canada Graph Database Market By Analysis Type
14.2.9.6 Canada Graph Database Market By End User
14.2.10 Mexico
14.2.10.1 Mexico Graph Database Market By Component
14.2.10.2 Mexico Graph Database Market By Deployment
14.2.10.3 Mexico Graph Database Market By Type
14.2.10.4 Mexico Graph Database Market By Application
14.2.10.5 Mexico Graph Database Market By Analysis Type
14.2.10.6 Mexico Graph Database Market By End User
14.3 Europe
14.3.1 Eastern Europe
14.3.1.1 Eastern Europe Graph Database Market By Country
14.3.1.2 Eastern Europe Graph Database Market By Component
14.3.1.3 Eastern Europe Graph Database Market By Deployment
14.3.1.4 Eastern Europe Graph Database Market By Type
14.3.1.5 Eastern Europe Graph Database Market By Application
14.3.1.6 Eastern Europe Graph Database Market By Analysis Type
14.3.1.7 Eastern Europe Graph Database Market By End User
13.3.1.8 Poland
14.3.1.8.1 Poland Graph Database Market By Component
14.3.1.8.2 Poland Graph Database Market By Deployment
14.3.1.8.3 Poland Graph Database Market By Type
14.3.1.8.4 Poland Graph Database Market By Application
14.3.1.8.5 Poland Graph Database Market By Analysis Type
14.3.1.8.6 Poland Graph Database Market By End User
14.3.1.9 Romania
14.3.1.9.1 Romania Graph Database Market By Component
14.3.1.9.2 Romania Graph Database Market By Deployment
14.3.1.9.3 Romania Graph Database Market By Type
14.3.1.9.4 Romania Graph Database Market By Application
14.3.1.9.5 Romania Graph Database Market By Analysis Type
14.3.1.9.6 Romania Graph Database Market By End User
14.3.1.10 Hungary
14.3.1.10.1 Hungary Graph Database Market By Component
14.3.1.10.2 Hungary Graph Database Market By Deployment
14.3.1.10.3 Hungary Graph Database Market By Type
14.3.1.10.4 Hungary Graph Database Market By Application
14.3.1.10.5 Hungary Graph Database Market By Analysis Type
14.3.1.10.6 Hungary Graph Database Market By End User
14.3.1.11 Turkey
14.3.1.11.1 Turkey Graph Database Market By Component
14.3.1.11.2 Turkey Graph Database Market By Deployment
14.3.1.11.3 Turkey Graph Database Market By Type
14.3.1.11.4 Turkey Graph Database Market By Application
14.3.1.11.5 Turkey Graph Database Market By Analysis Type
14.3.1.11.6 Turkey Graph Database Market By End User
14.3.1.12 Rest of Eastern Europe
14.3.1.12.1 Rest of Eastern Europe Graph Database Market By Component
14.3.1.12.2 Rest of Eastern Europe Graph Database Market By Deployment
14.3.1.12.3 Rest of Eastern Europe Graph Database Market By Type
14.3.1.12.4 Rest of Eastern Europe Graph Database Market By Application
14.3.1.12.5 Rest of Eastern Europe Graph Database Market By Analysis Type
14.3.1.12.6 Rest of Eastern Europe Graph Database Market By End User
14.3.2 Western Europe
14.3.2.1 Western Europe Graph Database Market By Country
14.3.2.2 Western Europe Graph Database Market By Component
14.3.2.3 Western Europe Graph Database Market By Deployment
14.3.2.4 Western Europe Graph Database Market By Type
14.3.2.5 Western Europe Graph Database Market By Application
14.3.2.6 Western Europe Graph Database Market By Analysis Type
14.3.2.7 Western Europe Graph Database Market By End User
14.3.2.8 Germany
14.3.2.8.1 Germany Graph Database Market By Component
14.3.2.8.2 Germany Graph Database Market By Deployment
14.3.2.8.3 Germany Graph Database Market By Type
14.3.2.8.4 Germany Graph Database Market By Application
14.3.2.8.5 Germany Graph Database Market By Analysis Type
14.3.2.8.6 Germany Graph Database Market By End User
14.3.2.9 France
14.3.2.9.1 France Graph Database Market By Component
14.3.2.9.2 France Graph Database Market By Deployment
14.3.2.9.3 France Graph Database Market By Type
14.3.2.9.4 France Graph Database Market By Application
14.3.2.9.5 France Graph Database Market By Analysis Type
14.3.2.9.6 France Graph Database Market By End User
14.3.2.10 UK
14.3.2.10.1 UK Graph Database Market By Component
14.3.2.10.2 UK Graph Database Market By Deployment
14.3.2.10.3 UK Graph Database Market By Type
14.3.2.10.4 UK Graph Database Market By Application
14.3.2.10.5 UK Graph Database Market By Analysis Type
14.3.2.10.6 UK Graph Database Market By End User
14.3.2.11 Italy
14.3.2.11.1 Italy Graph Database Market By Component
14.3.2.11.2 Italy Graph Database Market By Deployment
14.3.2.11.3 Italy Graph Database Market By Type
14.3.2.11.4 Italy Graph Database Market By Application
14.3.2.11.5 Italy Graph Database Market By Analysis Type
14.3.2.11.6 Italy Graph Database Market By End User
14.3.2.12 Spain
14.3.2.12.1 Spain Graph Database Market By Component
14.3.2.12.2 Spain Graph Database Market By Deployment
14.3.2.12.3 Spain Graph Database Market By Type
14.3.2.12.4 Spain Graph Database Market By Application
14.3.2.12.5 Spain Graph Database Market By Analysis Type
14.3.2.12.6 Spain Graph Database Market By End User
14.3.2.13 The Netherlands
14.3.2.13.1 Netherlands Graph Database Market By Component
14.3.2.13.2 Netherlands Graph Database Market By Deployment
14.3.2.13.3 Netherlands Graph Database Market By Type
14.3.2.13.4 Netherlands Graph Database Market By Application
14.3.2.13.5 Netherlands Graph Database Market By Analysis Type
14.3.2.13.6 Netherlands Graph Database Market By End User
14.3.2.14 Switzerland
14.3.2.14.1 Switzerland Graph Database Market By Component
14.3.2.14.2 Switzerland Graph Database Market By Deployment
14.3.2.14.3 Switzerland Graph Database Market By Type
14.3.2.14.4 Switzerland Graph Database Market By Application
14.3.2.14.5 Switzerland Graph Database Market By Analysis Type
14.3.2.14.6 Switzerland Graph Database Market By End User
14.3.2.15 Austria
14.3.2.15.1 Austria Graph Database Market By Component
14.3.2.15.2 Austria Graph Database Market By Deployment
14.3.2.15.3 Austria Graph Database Market By Type
14.3.2.15.4 Austria Graph Database Market By Application
14.3.2.15.5 Austria Graph Database Market By Analysis Type
14.3.2.15.6 Austria Graph Database Market By End User
14.3.2.16 Rest of Western Europe
14.3.2.16.1 Rest of Western Europe Graph Database Market By Component
14.3.2.16.2 Rest of Western Europe Graph Database Market By Deployment
14.3.2.16.3 Rest of Western Europe Graph Database Market By Type
14.3.2.16.4 Rest of Western Europe Graph Database Market By Application
14.3.2.16.5 Rest of Western Europe Graph Database Market By Analysis Type
14.3.2.16.5 Rest of Western Europe Graph Database Market By End User
14.4 Asia-Pacific
14.4.1 Asia Pacific Graph Database Market By Country
14.4.2 Asia Pacific Graph Database Market By Component
14.4.3 Asia Pacific Graph Database Market By Deployment
14.4.4 Asia Pacific Graph Database Market By Type
14.4.5 Asia Pacific Graph Database Market By Application
14.4.6 Asia Pacific Graph Database Market By Analysis Type
14.4.7 Asia Pacific Graph Database Market By End User
14.4.8 China
14.4.8.1 China Graph Database Market By Component
14.4.8.2 China Graph Database Market By Deployment
14.4.8.3 China Graph Database Market By Type
14.4.8.4 China Graph Database Market By Application
14.4.8.5 China Graph Database Market By Analysis Type
14.4.8.6 China Graph Database Market By End User
14.4.9 India
14.4.9.1 India Graph Database Market By Component
14.4.9.2 India Graph Database Market By Deployment
14.4.9.3 India Graph Database Market By Type
14.4.9.4 India Graph Database Market By Application
14.4.9.5 India Graph Database Market By Analysis Type
14.4.9.6 India Graph Database Market By End User
14.4.10 Japan
14.4.10.1 Japan Graph Database Market By Component
14.4.10.2 Japan Graph Database Market By Deployment
14.4.10.3 Japan Graph Database Market By Type
14.4.10.4 Japan Graph Database Market By Application
14.4.10.5 Japan Graph Database Market By Analysis Type
14.4.10.6 Japan Graph Database Market By End User
14.4.11 South Korea
14.4.11.1 South Korea Graph Database Market By Component
14.4.11.2 South Korea Graph Database Market By Deployment
14.4.11.3 South Korea Graph Database Market By Type
14.4.11.4 South Korea Graph Database Market By Application
14.4.11.5 South Korea Graph Database Market By Analysis Type
14.4.11.6 South Korea Digital Experience Platform By End User
14.4.12 Vietnam
14.4.12.1 Vietnam Graph Database Market By Component
14.4.12.2 Vietnam Graph Database Market By Deployment
14.4.12.3 Vietnam Graph Database Market By Type
14.4.12.4 Vietnam Graph Database Market By Application
14.4.12.5 Vietnam Graph Database Market By Analysis Type
14.4.12.6 Vietnam Graph Database Market By End User
14.4.13 Singapore
14.4.13.1 Singapore Graph Database Market By Component
14.4.13.2 Singapore Graph Database Market By Deployment
14.4.13.3 Singapore Graph Database Market By Type
14.4.13.4 Singapore Graph Database Market By Application
14.4.13.5 Singapore Graph Database Market By Analysis Type
14.4.13.6 Singapore Graph Database Market By End User
14.4.14 Australia
14.4.14.1 Australia Graph Database Market By Component
14.4.14.2 Australia Graph Database Market By Deployment
14.4.14.3 Australia Graph Database Market By Type
14.4.14.4 Australia Graph Database Market By Application
14.4.14.5 Australia Graph Database Market By Analysis Type
14.4.14.6 Australia Graph Database Market By End User
14.4.15 Rest of Asia-Pacific
14.4.15.1 APAC Graph Database Market By Component
14.4.15.2 APAC Graph Database Market By Deployment
14.4.15.3 APAC Graph Database Market By Type
14.4.15.4 APAC Graph Database Market By Application
14.4.15.5 APAC Graph Database Market By Analysis Type
14.4.15.6 APAC Graph Database Market By End User
14.5 The Middle East & Africa
14.5.1 Middle East
14.5.1.1 Middle East Graph Database Market By country
14.5.1.2 Middle East Graph Database Market By Component
14.5.1.3 Middle East Graph Database Market By Deployment
14.5.1.4 Middle East Graph Database Market By Type
14.5.1.5 Middle East Graph Database Market By Application
14.5.1.6 Middle East Graph Database Market By Analysis Type
14.5.1.7 Middle East Graph Database Market By End User
14.5.1.8 UAE
14.5.1.8.1 UAE Graph Database Market By Component
14.5.1.8.2 UAE Graph Database Market By Deployment
14.5.1.8.3 UAE Graph Database Market By Type
14.5.1.8.4 UAE Graph Database Market By Application
14.5.1.8.5 UAE Graph Database Market By Analysis Type
14.5.1.8.6 UAE Graph Database Market By End User
14.5.1.9 Egypt
14.5.1.9.1 Egypt Graph Database Market By Component
14.5.1.9.2 Egypt Graph Database Market By Deployment
14.5.1.9.3 Egypt Graph Database Market By Type
14.5.1.9.4 Egypt Graph Database Market By Application
14.5.1.9.5 Egypt Graph Database Market By Analysis Type
14.5.1.9.6 Egypt Graph Database Market By End User
14.5.1.10 Saudi Arabia
14.5.1.10.1 Saudi Arabia Graph Database Market By Component
14.5.1.10.2 Saudi Arabia Graph Database Market By Deployment
14.5.1.10.3 Saudi Arabia Graph Database Market By Type
14.5.10.4 Saudi Arabia Graph Database Market By Application
14.5.10.5 Saudi Arabia Graph Database Market By Analysis Type
14.5.10.6 Saudi Arabia Graph Database Market By End User
14.5.1.11 Qatar
14.5.1.11.1 Qatar Graph Database Market By Component
14.5.1.11.2 Qatar Graph Database Market By Deployment
14.5.1.11.3 Qatar Graph Database Market By Type
14.5.1.11.4 Qatar Graph Database Market By Application
14.5.1.11.5 Qatar Graph Database Market By Analysis Type
14.5.1.11.6 Qatar Graph Database Market By End User
14.5.1.12 Rest of Middle East
14.5.1.12.1 Rest of Middle East Graph Database Market By Component
14.5.1.12.2 Rest of Middle East Graph Database Market By Deployment
14.5.1.12.3 Rest of Middle East Graph Database Market By Type
14.5.1.12.4 Rest of Middle East Graph Database Market By Application
14.5.1.12.5 Rest of Middle East Graph Database Market By Analysis Type
14.5.1.12.6 Rest of Middle East Graph Database Market By End User
14.5.2 Africa
14.5.2.1 Africa Graph Database Market By Country
14.5.2.2 Africa Graph Database Market By Component
14.5.2.3 Africa Graph Database Market By Deployment
14.5.2.4 Africa Graph Database Market By Type
14.5.2.5 Africa Graph Database Market By Application
14.5.2.6 Africa Graph Database Market By Analysis Type
14.5.2.7 Africa Graph Database Market By End User
14.5.2.8 Nigeria
14.5.2.8.1 Nigeria Graph Database Market By Component
14.5.2.8.2 Nigeria Graph Database Market By Deployment
14.5.2.8.3 Nigeria Graph Database Market By Type
14.5.2.8.4 Nigeria Graph Database Market By Application
14.5.2.8.5 Nigeria Graph Database Market By Analysis Type
14.5.2.8.6 Nigeria Graph Database Market By End User
14.5.2.9 South Africa
14.5.2.9.1 South Africa Graph Database Market By Component
14.5.2.9.2 South Africa Graph Database Market By Deployment
14.5.2.9.3 South Africa Graph Database Market By Type
14.5.2.9.4 South Africa Graph Database Market By Application
14.5.2.9.5 South Africa Graph Database Market By Analysis Type
14.5.2.9.6 South Africa Graph Database Market By End User
14.5.2.10 Rest of Africa
14.5.2.10.1 Rest of Africa Graph Database Market By Component
14.5.2.10.2 Rest of Africa Graph Database Market By Deployment
14.5.2.10.3 Rest of Africa Graph Database Market By Type
14.5.2.10.4 Rest of Africa Graph Database Market By Application
14.5.2.10.5 Rest of Africa Graph Database Market By Analysis Type
14.5.2.10.6 Rest of Africa Graph Database Market By End User
14.6 Latin America
14.6.1 Latin America Graph Database Market By Country
14.6.2 Latin America Graph Database Market By Component
14.6.3 Latin America Graph Database Market By Deployment
14.6.4 Latin America Graph Database Market By Type
14.6.5 Latin America Graph Database Market By Application
14.6.6 Latin America Graph Database Market By Analysis Type
14.6.7 Latin America Graph Database Market By End User
14.6.8 Brazil
14.6.8.1 Brazil Graph Database Market By Component
14.6.8.2 Brazil Africa Graph Database Market By Deployment
14.6.8.3Brazil Graph Database Market By Type
14.6.8.4 Brazil Graph Database Market By Application
14.6.8.5 Brazil Graph Database Market By Analysis Type
14.6.8.5 Brazil Graph Database Market By End User
14.6.9 Argentina
14.6.9.1 Argentina Graph Database Market By Component
14.6.9.2 Argentina Graph Database Market By Deployment
14.6.9.3 Argentina Graph Database Market By Type
14.6.9.4 Argentina Graph Database Market By Application
14.6.9.5 Argentina Graph Database Market By Analysis Type
14.6.9.6 Argentina Graph Database Market By End User
14.6.10 Colombia
14.6.10.1 Colombia Graph Database Market By Component
14.6.10.2 Colombia Graph Database Market By Deployment
14.6.10.3 Colombia Graph Database Market By Type
14.6.10.4 Colombia Graph Database Market By Application
14.6.10.5 Colombia Graph Database Market By Analysis Type
14.6.10.6 Colombia Graph Database Market By End User
14.6.11 Rest of Latin America
14.6.11.1 Rest of Latin America Graph Database Market By Component
14.6.11.2 Rest of Latin America Graph Database Market By Deployment
14.6.11.3 Rest of Latin America Graph Database Market By Type
14.6.11.4 Rest of Latin America Graph Database Market By Application
14.6.11.5 Rest of Latin America Graph Database Market By Analysis Type
14.6.11.6 Rest of Latin America Graph Database Market By End User
15 Company Profile
15.1 Oracle Corporation
15.1.1 Company Overview
15.1.2 Financials
15.1.3 Product/ Services Offered
15.1.4 SWOT Analysis
15.1.5 The SNS View
15.2 Orient DB.
15.2.1 Company Overview
15.2.2 Financials
15.2.3 Product/ Services Offered
15.2.4 SWOT Analysis
15.2.5 The SNS View
15.3 Hewlett Packard Enterprise.
15.3.1 Company Overview
15.3.2 Financials
15.3.3 Product/ Services Offered
15.3.4 SWOT Analysis
15.3.5 The SNS View
15.4 Microsoft Corporation.
15.4.1 Company Overview
15.4.2 Financials
15.4.3 Product/ Services Offered
15.4.4 SWOT Analysis
15.4.5 The SNS View
15.5 Teradata Corporation
15.5.1 Company Overview
15.5.2 Financials
15.5.3 Product/ Services Offered
15.5.4 SWOT Analysis
15.5.5 The SNS View
15.6 Stardog Union Inc.
15.6.1 Company Overview
15.6.2 Financials
15.6.3 Product/ Services Offered
15.6.4 SWOT Analysis
15.6.5 The SNS View
15.7 Amazon Web Services, Inc.
15.7.1 Company Overview
15.7.2 Financials
15.7.3 Product/ Services Offered
15.7.4 SWOT Analysis
15.7.5 The SNS View
15.8 Objectivity Inc.
15.8.1 Company Overview
15.8.2 Financials
15.8.3 Product/ Services Offered
15.8.4 SWOT Analysis
15.8.5 The SNS View
15.9 TIBCO Software.
15.9.1 Company Overview
15.9.2 Financials
15.9.3 Product/ Services Offered
15.9.4 SWOT Analysis
15.9.5 The SNS View
15.10 IBM Corporation.
15.10.1 Company Overview
15.10.2 Financials
15.10.3 Product/ Services Offered
15.10.4 SWOT Analysis
15.10.5 The SNS View
16. Competitive Landscape
16.1 Competitive Benchmarking
16.2 Market Share Analysis
16.3 Recent Developments
16.3.1 Industry News
16.3.2 Company News
16.3.3 Mergers & Acquisitions
17. USE Cases and Best Practices
18. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
The Digital Transaction Management Market size was USD 9.92 billion in 2022 and is expected to Reach USD 62.38 billion by 2030 and grow at a CAGR of 25.84 % over the forecast period of 2023-2030.
The POS Security Market size was USD 4.54 Billion in 2023 and is expected to Reach USD 8.59 Billion by 2031 and grow at a CAGR of 8.3% over the forecast period of 2024-2031.
Digital Payments Market size was valued at USD 98.2 Bn in 2023 and is expected to reach USD 436.1 Bn by 2031, and grow at a CAGR of 20.48 % over the forecast period 2024-2031.
The Online Tutoring Services Market Size was valued at USD 8.84 Billion in 2023 and is expected to reach USD 26.31 Billion by 2031 and grow at a CAGR of 14.6% over the forecast period 2024-2031.
The Enterprise Social Software Market size was valued at USD 9.96 billion in 2022 and is expected to hit USD 45.91 billion by 2030 with a growing CAGR of 21.05% over the forecast period of 2023-2030.
The 5G Fixed Wireless Access (FWA) Market size was valued at USD 24.66 Bn in 2022 and is expected to reach USD 337.75 Bn by 2030, and grow at a CAGR of 38.7% over the forecast period 2023-2030.
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