GraphAware Blog

Find out what's new in the world of mission-critical graph analytics.

Using the Neo4j Shell with Embedded Neo4j

10 Feb 2015 by Luanne Misquitta · 1 min read Neo4j Intermediate

Our earlier blog posttalked about using the Neo4j web browser along with embedded Neo4j.The WrappingNeoServerBootstrapper which was employed to do this has been deprecated for a while and it raises questionsabout the alternative.

Using the Neo4j Browser with Embedded Neo4j

21 Nov 2014 by Luanne Misquitta · 1 min read Neo4j Intermediate

There are times when you have an application using Neo4j in embedded mode but also need to play around with the graphusing the Neo4j web browser. Since the database can be accessed from at most one process at a time, trying to start upthe Neo4j server when your embedded Neo4j application is running won’t work. The WrappingNeoServerBootstrapper,although deprecated, comes to the rescue. Here’s how to set it up.

GraphAware Neo4j ChangeFeed

27 Aug 2014 by Luanne Misquitta · 0 min read

In this post, we’d like to introduce the first version of the GraphAware Neo4j ChangeFeed - a GraphAware Runtime Modulethat keeps track of changes made to the graph.

GraphAware Neo4j TimeTree

20 Aug 2014 by Luanne Misquitta, Michal Bachman · 0 min read

Modelling and querying time-based events in a graph is a fairly common discussion topic and a frequently asked questionon Q/A sites. In this blog post, we evaluate some of the common approaches and introduce GraphAware TimeTree, a GraphAware Framework Module that simplifies modelling time and events in Neo4j.

Random Graph Models (Part II)

06 Aug 2014 by Vojtěch Havlíček · 4 min read Neo4j GraphAware Intermediate

In the first part of this short series aboutrandom graph models, we talked about why they are useful and had a brief look at two of them: Erdos-Renyi graphs andBarabasi-Albert model. In this post, we take a look at the “small world” phenomenon and another network model, namelythe Watts-Strogatz model.

Node Degrees in Neo4j 2.1

23 Jul 2014 by Michal Bachman · 3 min read Neo4j GraphAware Beginner

Efficient counting of relationships in Neo4j was the cornerstone of my Master Thesisand the reason the very first GraphAware Frameworkmodule called the Relationship Count Module was born. The improvements in Neo4j 2.1around dense nodes and the addition of getDegree(…) methods on the Node interface made me eager to do some benchmarking around relationship counts again.

Random Graph Models (Part I)

16 Jul 2014 by Vojtěch Havlíček · 4 min read Neo4j GraphAware Intermediate

When one obtains a graph data from a measurement on a real world network, it is sometimes useful to make comparison witha random graph. Such graph is characterised by certain degree distribution, which you can imagine to be a list of degreesof nodes present in the network. The most interesting distributions have certain functional dependence which allowsone to infer what processes are dominant in formation of the network. The processes consequently characterise therelationships between the nodes.