Introduction

Real-time recommendations are becoming more important than ever. But this requires the ability to correlate product information, customer inventory, past customer behaviour, current supplier information, logistics, and even social data such as ads clicked and products explored via social media. This is extremely difficult for certain kinds of databases. .

The technology for collecting all of this data and forming connections to gain speedy insight into customer needs and product trends—and then to provide real-time .
recommendations—is the graph database. In fact, many large corporations rely upon graph analytics to provide their recommendations because the relationships are already laid out, and analysis of these relationships to provide recommendations is very fast. AI allows Graph to train and deploy models automatically without prior manual intervention. Inherent topologies, connections forms natural groups, cliques to find similarities for more contextual and personalized recommendations