“Increasing Adoption of Cloud-Based Graph Databases”
- A significant and accelerating trend in the global graph database market is the increasing adoption of cloud-based deployment models, enabling enhanced scalability, flexibility, and real-time collaboration across distributed data environments
- For instance, Amazon Neptune, a fully managed graph database service on AWS, supports both RDF and Property Graph models and is widely used for knowledge graphs and fraud detection. Similarly, Microsoft’s Azure Cosmos DB provides native support for Gremlin API, enabling scalable graph database solutions in the cloud
- Cloud-based graph databases allow organizations to manage massive volumes of connected data with minimal infrastructure overhead, enabling faster deployment and easier integration with existing cloud-native services. Google Cloud’s integration with Neo4j AuraDB allows users to build advanced analytics and recommendation engines without managing backend systems
- These platforms support use cases such as identity access management, real-time fraud analysis, and personalized content delivery by leveraging relationship-centric data modeling in a cost-effective, on-demand environment
- This shift toward cloud-native graph solutions is fundamentally reshaping how businesses derive insights from complex data. Companies such as Neo4j and TigerGraph are actively expanding their cloud offerings to meet rising demand from sectors including BFSI, telecom, and retail
- The demand for cloud-based graph databases is accelerating rapidly as enterprises seek to modernize data infrastructure, improve time-to-insight, and achieve seamless integration with AI and machine learning workflows
Frequently Asked Questions
The market is segmented based on Segmentation, By Type (Resource Description Framework (RDF) and Labeled Property Graph (LPG)), Application (Fraud Detection, Prevention, and Recommendation Engine), Database (Relational (SQL) and Non-relational (NoSQL)), Deployment Model (On-premise and Cloud), Analysis Type (Path Analysis, Connectivity Analysis, Community Analysis, and Centrality Analysis), Size (Large Enterprises, Small and Medium Enterprises), Component (Software and Services), End User (Banking, Financial Services and Insurance, Telecom and IT, Healthcare and Lifesciences, Transportation and Logistics, Retail and E-commerce, Energy and Utilities, Government and Public, Manufacturing, and Others) - Industry Trends and Forecast to 2032
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The Global Graph Database Market size was valued at USD 2.70 USD Billion in 2024.
The Global Graph Database Market is projected to grow at a CAGR of 18.2% during the forecast period of 2025 to 2032.
The major players operating in the market include Teradata , Hewlett Packard Enterprise Development LP , IBM Corporation , Microsoft , Siemens AG , ANSYSInc , SAP SE , Oracle , Robert Bosch GmbH , Swim.aiInc. ., Atos S.E. , ABB , KELLTON TECH , AVEVA Group plc , DXC Technology Company , Altair EngineeringInc , Hexaware Technologies Limited , Tata Consultancy Services Limited , Infosys Limited , NTT DATAInc. , TIBCO Software Inc. , Redis Ltd .
The market report covers data from the North America.
