GRAPH DATABASE
Database designed to treat the relationship between data the same the importance of the data itself.
About Graph Database
Graph Database is a database designed to treat the relationship between data the same the importance of the data itself. This is meant to store data without limiting it to models previously determined. As a replacement, the data is saved like the first time we draw it shows how each individual entity connected with or related to another entity.
When Connected Data Matters Most
Early graph innovators have already pioneered the most popular use cases – fraud detection, personalization, customer 360, knowledge graphs, network management, and more.
Fraud Detection & Analytics, real-time analysis of data relationships is essential to uncovering fraud rings and other sophisticated scams before fraudsters and criminals cause lasting damage.
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Network and Database Infrastructure Monitoring for IT Operations, graph databases are inherently more suitable than RDBMS for making sense of complex interdependencies central to managing networks and IT infrastructure.
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Recommendation Engine & Product Recommendation System, graph-powered recommendation engines help companies personalize products, content and services by leveraging a multitude of connections in real time.
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Master Data Management, organize and manage your master data with the flexible and schema-free graph database model in order to get real-time insights and a 360° view of your customers.
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Identity & Access Management, quickly and effectively track users, assets, relationships and authorizations when you use a graph database for identity and access management.
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Artificial Intelligence and Analytics, Artificial Intelligence (AI) is poised to drive the next wave of technological disruption across nearly every industry. Just like previous technology revolutions in web and mobile.
Data Privacy, Risk and Compliance, fast and effective regulatory compliance (GDPR, CCPA, BCBS 239, FRTB…). Manage enterprise risk while leveraging connected data to drive better business intelligence
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Financial Services, from risk management to securities recommendations, context is key. Find out why top banks across the globe are using Neo4j to solve their connected data challenges.
