The common domain implementation pattern when using Neo4j is to let the domain objects wrap a node, and store the state of the entity in the node properties. To relieve you from the boilerplate code needed for this, you can use a framework like jo4neo (intro, blog posts), where you use annotations to declare properties and relationships, but still have the full power of the graph database available for deep traversals and other graphy stuff. Here's a code sample showing jo4neo in action:view sourceprint?public class Person {  //used by jo4neo  transient Nodeid node;  //simple property  @neo String firstName;  //helps you store a java.util.Date to neo4j  @neo Date date;  // jo4neo will index for you  @neo(index=true) String email;  // many to many relation  @neo Collection<role> roles;    /* normal class oriented  * programming stuff goes here  */}</role>

Gremlin is a Turing Complete programming language useful for working with graphs. It is a Java DSL that makes extensive use of XPath to query, analyze and manipulate graphs. Gremlin can be used to create multi-relational graphs. Because the elements of the graph, vertices and edges, have properties defined as key-value pairs, the graph is called a property graph, and this is an example: The language has the following types: graph: a graph is composed of a set of vertices and a set of edges. vertex: a vertex is composed of a set of outgoing edges, incoming edges, and a map of properties. edge: an edge is composed of an outgoing vertex, incoming vertex, and a map of properties. boolean: a boolean can either be true or false. number: a number is a natural (integer) or real (double) number. string: a string is an array of characters. list: a list is an ordered collection of potentially duplicate objects. map: a map is an associative array from a set of object keys to a c

Neo4j addresses the problem of performance degradation over queries that involve many joins in a traditional RDBMS. By modeling the data around graphs, Neo4j can traverse along nodes and edges with the same speed, independently of the amount of data constituting the graph. This gives secondary effects like very fast graph algos, recommender systems and OLAP-style analytics that are currently not possible with normal RDBMS setups.

We are shifting from pushing information to pulling it. Media companies know that they will have to give their consumers full control to pull stories, news, music, television, movies, and all their content to them when they want it, where they want it, the way they want it. This shift is coming to all industries, from medicine to banking to cars and toys. 2.    The shift has already begun. The financial reporting industry has already embraced the semantic web and has built the largest commercial ecosystem of online, interoperable data so far. Many other industries are gearing up to follow. Your industry is no exception. 3.    Products will be pulled. As you take a product off the shelf, you’ll be pulling on the entire supply chain, causing a ripple effect back to the manufacturer. Your customers will start pulling your products from you, rather than you pushing them. Customers will be much more involved in product development; cycles will shorten dramatically. 4.    Big hint: This goes for marketing, too. Push marketing will become less and less relevant. Customers will say what they are looking for and you will have to respond on their terms, not yours. 5.    Services will be pulled as well. A building will order its own supplies and maintenance services. Your services may be combined with those of your competitor without you even knowing it. Customers will dictate the terms and you will have to go along. 6.    Most business processes will invert. The sales-oriented or solutions-oriented culture many companies have will be much less profitable, as market and customer-driven processes rise. Customers will soon be in a position to enter their desires in a way that can fit into your manufacturing or production processes directly. 7.    Customers will become ten times more powerful!They will keep the customer-relationship on their side. Projects like the VRM (Vendor Relationship Management) Project at Harvard and OpenID will put customers much more in charge. 8.    Pulling will have a profound impact on our entire economy. More than $3 trillion of our economy will be affected. Everything from retail to health care to the IRS will be streamlined by the principles of pull. 9.    Watch for the warning signs of push cancer. Push is about vendor lock-in and proprietary data strategies. Apple and Facebook are push companies—they will both face strong competition from the open web. They will both have to change their cultures to embrace pull or they will become much smaller. 10.   Watch for the signs of pull. Pull is the natural way businesses should work to put the customer first. When you hear about companies opening their data, giving customers account portability, and talking about interoperability with competitors, that’s the language of pull. Google embraces some of the principles of pull, but we’ll see how far they go. There is a lot at stake—learn now to open your corporate culture to the principles that will shape successful 21st century companies.

These pages will guide you through an example web application using the IMDB dataset. The aim is to show an example web application with an architecture based on Spring, which is close to what a real life example could look like.

Im sure a lot of you out there have heard the term Web 2.0, but today I wanted to explain Web 3.0. Web 3.0 is a very interesting term that talks about the semantic web. The below image better explains the differences between Web 1.0, Web 2.0 and Web 3.0. Web 1.0 – Web 1.0 was all about static content which was read-only. Best examples of web 1.0 was geocities and hotmail, which both have great static html websites with read-only content. People preferred navigating the web through link directories of Yahoo! and dmoz. Web 2.0 – Web 2.0 is about user generated content and the read-write web. People are consuming as well as contributing information through blogs or sites like Flickr, YouTube, Digg, etc. The line dividing a consumer and content publisher is increasingly getting blurred in the Web 2.0 era. Web 3.0 – This will be about semantic web (or the meaning of data), personalization (e.g. iGoogle), intelligent search and behavioral advertising among other things.