Entrendipity (Entrendipity) On Graph Computing. The concept of a graph has been around since the dawn of mechanical computing and for many decades prior in the domain of pure mathematics.
Due in large part to this golden age of databases, graphs are becoming increasingly popular in software engineering. Graph databases provide a way to persist and process graph data. However, the graph database is not the only way in which graphs can be stored and analyzed. Graph computing has a history prior to the use of graph databases and has a future that is not necessarily entangled with typical database concerns. There are numerous graph technologies that each have their respective benefits and drawbacks. Graph Theory.
Visualize. A lightweight JavaScript graph drawing library. JavaScript InfoVis Toolkit. Scalable Graph Clustering with Pregel by Chris McCubbin on Prezi. The Open Graph Protocol Design Decisions. Networks, Crowds, and Markets: A Book by David Easley and Jon Kleinberg. In recent years there has been a growing public fascination with the complex "connectedness" of modern society.
This connectedness is found in many incarnations: in the rapid growth of the Internet and the Web, in the ease with which global communication now takes place, and in the ability of news and information as well as epidemics and financial crises to spread around the world with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else. Networks, Crowds, and Markets combines different scientific perspectives in its approach to understanding networks and behavior. The book is based on an inter-disciplinary course that we teach at Cornell. The book, like the course, is designed at the introductory undergraduate level with no formal prerequisites.
Design your application using Persistent Graphs and OrientDB.