Do you use D3 for data visualisation and either you are considering, or already using it also for graph visualisation? Keep in mind that D3 uses SVG for rendering. While it is the easiest to work with API for drawing 2D graphics on the Web, its downside is that the browser keeps the entire DOM tree of vector elements in memory, even for elements that are effectively invisible. You might hit a performance drop with complex graphics, specifically for graph visualisation when you try drawing graphs larger than ~1000 nodes, or even less with complex SVG effects.
The Cypher query planner is quite advanced and mature, and you can mostly rely on it to pick the best plan for your query. However, there are rare cases, or bugs, that might want you looking for ways to influence that plan. This article demonstrates practical usage of an index hint.
As of version 2.1, Neo4j OGM will support persistence events. Although a date for the release of 2.1 isn’t known at thetime of writing, we think this is an important and exciting new feature and so we’ll be writing a series of posts aboutit over the next few weeks to whet your appetites. In this first post we’ll take a quick tour of the new Events mechanismin the OGM, and provide some examples of how we might use it in our own applications. But first, some background…
For most organisations, data security is extremely important. The topic comes up every single time we are training, consulting,or otherwise engaging in the world of graphs and Neo4j. At the same time, security is very difficult and time-consuming to get rightand the implications of getting it wrong can be serious. In this blog post, we introduce the integration of Spring Securityinto Neo4j which provides important security controls and mechanisms for enterprises and governments that make use of theworld’s most popular graph database.
At GraphAware, we help organisations in a wide range of verticals solve problems with graphs.Once we come across a requirement or use case two or three different times, we typically create an open-source Neo4j extensionthat addresses it. The latest addition to our product portfolio, introduced in this post, is a simple library that automaticallyexpires data from the Neo4j graph database.
Last weekend, I came across a tweet announcing that Wikimedia released the dataset of the page clickstreamsfor February 2015. I found it interesting to download this dataset and see how people arrive on the Neo4j’s Wikipedia page.
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.
A common question when planning and designing your Neo4j Graph Database is how to handle “flagged” entities. This couldinclude users that are active, blog posts that are published, news articles that have been read, etc.
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.
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.
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.