The first part of this article introduced Neo4j and its Cypher Query Language. If you’ve read Part 1, you’ve seen for yourself why Neo4j and other graph databases are especially popular for social graphing, or modeling relationships between users in a network. You also got Neo4j setup in your development environment, and you got an overview of the basic concepts of working with this data store–namely nodes and relationships.
We then used the Cypher Query Language to model a family in Neo4j, including personal attributes like age, gender, and the relationships between family members. We created some friends to broaden our social graph, then added key/value pairs to generate a list of movies that each user had seen. Finally, we queried our data, using graph analytics to search for a movie that one user had not seen but might enjoy.
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