The objective of BigGraphs is to provide a distributed middleware for very large graphs processing. The first phase of the project consists in the evaluation of the existing middlewares such as GraphX/Spark or Giraph/Hadoop with respect to the following criteria: ease of deployment, maintenance and use, variety of programming models (Map/Reduce, BSP, (a)synchronous message passing, centralized programming, mobile agent-based, etc.), overall efficiency and memory footprint, etc. One of the chosen use cases is a subgraph of the Twitter graph with 3 millions of nodes and 200 millions of edges. The experiments are run on the NEF cluster at Inria. We have implemented and tested the classic algorithms (using the BSP model): page rank, BFS, connected components as well as the iFUB algorithm for computing the diameter of large graphs.