GraphChi promises in part:
The promise of GraphChi is to bring web-scale graph computation, such as analysis of social networks, available to anyone with a modern laptop.
Well, that certainly draws a line in the sand doesn’t it?
A bit more from the introduction:
GraphChi is a spin-off of the GraphLab ( http://www.graphlab.org ) -project from the Carnegie Mellon University. It is based on research by Aapo Kyrola ( http://www.cs.cmu.edu/~akyrola/) and his advisors.
GraphChi can run very large graph computations on just a single machine, by using a novel algorithm for processing the graph from disk (SSD or hard drive). Programs for GraphChi are written in the vertex-centric model, proposed by GraphLab and Google's Pregel. GraphChi runs vertex-centric programs asynchronously (i.e changes written to edges are immediately visible to subsequent computation), and in parallel. GraphChi also supports streaming graph updates and removal of edges from the graph. Section 'Performance' contains some examples of applications implemented for GraphChi and their running times on GraphChi.
The promise of GraphChi is to bring web-scale graph computation, such as analysis of social networks, available to anyone with a modern laptop. It saves you from the hassle and costs of working with a distributed cluster or cloud services. We find it much easier to debug applications on a single computer than trying to understand how a distributed algorithm is executed.
In some cases GraphChi can solve bigger problems in reasonable time than many other available distributed frameworks. GraphChi also runs efficiently on servers with plenty of memory, and can use multiple disks in parallel by striping the data.
Even if you do require the processing power of high-performance clusters, GraphChi can be an excellent tool for developing and debugging your algorithms prior to deploying them to the cluster. For high-performance graph computation in the distributed setting, we direct you to GraphLab's new version (v2.1), which can now handle large graphs in astonishing speed. GraphChi supports also most of the new GraphLab v2.1 API (with some restrictions), making the transition easy.
GraphChi is implemented in plain C++, and available as open-source under the flexible Apache License 2.0.
Java version
Java-version of GraphChi: http://code.google.com/p/graphchi-java
The performance numbers are impressive.
Not sure I would want to run production code on a laptop in any case but performance should be enough for on-the-road experiments.
Good documentation and examples that should ease you into experimenting with GraphChi.
I first saw this at High Scalability.