GraphAware Blog

Our previous article demonstrated how easy it was to build an application using Spring Data Neo4j 4.

We are delighted to invite you to a Meetup on 4th February 2016 at 6:30 pm at GraphAware London office where Michal Bachman is going to present the European premiere of his talk entitled “Real-Time Recommendations and the Future of Search” combined with a unique expert panel discussion and Q&A.

This guide (first published on Airpair) will get you up and running with Spring Data Neo4j 4 in under an hour.

Iterating over large numbers of nodes using Cypher is quite a common use case in Neo4j. Typically, the reason for doing thisis that we want to perform some kind of operation for each one of these nodes. In this blog post, we will use one millionTestNodes and try to iterate over them in order to index their contents into a freshly created Elasticsearch index.There are three approaches we can take, two of which are quite common, but the most performant technique is largely unknown.

Last month, I had the pleasure of speaking at GraphConnect in San Francisco, introducing the Graph-Aided Search to alarge audience of Neo4j users and graph enthusiasts. For those who missed the conference, the recording and slides havenow been made available. Enjoy and get in touch with feedback / questions!

Recently, Neo Technology announced the 2.3.0-RC1 release of their Neo4j graph database. One of the key new features is TriadicSelection built into Cypher’s Cost Based Planner. In this blog post, we will explore the Triadic Selection in detailand demonstrate how significantly it can speed up recommendations computed in Neo4j.

For the last couple of years, Neo4j has been increasingly popular as the technology of choice for people building real-time recommendation engines. Having been at the forefront of the graph movement through clientengagements and open-source software development, we have identified the next step in the natural evolution of graph-based recommendationengines. We call it Graph-Aided Search.

Drawing a graph on a whiteboard is easy and fun! Translating that graph into an object model can sometimes result in questions such as “do I have to define relationships in both participating node entities?”or “which end of the relationship should I save?”.

Writing integration tests for your code that runs against Neo4j is simple enough when using the native API, but there’snot a great deal of help out there if you’re working in client-server mode. Making assertions about the shape of thegraph can also be difficult, particularly if use cases involve more than a few nodes and relationships.

In this blog post, we’ll demonstrate how to use variable length relationships (sometimes called “variable length paths”)in Cypher using examples. We will also see when zero length relationships can be useful.