Sector is an open source cloud written in C++ for storing, sharing and processing large data sets.   Sector is broadly similar to the Google File System and the Hadoop Distributed File System, except that it is designed to utilize wide area high performance  networks.

Sphere is middleware that is designed to process data managed by Sector.  Sphere implements a framework for distributed computing that allows any User Defined Function (UDF) to be applied to a Sector dataset.

One way to think about this is as a generalized MapReduce. With MapReduce, users work with pairs and define a Map function and a Reduce function, and the MapReduce application creates a workflow consisting of a Map, Shuffle, Sort and Reduce. With Sector, users can create a workflow consisting of any sequence of User Define Functions (UDFs) and apply these to any datasets managed by Sector. In particular, Sphere has predefined Shuffle and Sort UDFs that can be applied to datasets consisting of pairs so that MapReduce applications can be implemented once a user defines a Map and Reduce UDF.

Sector also implements security and we are currently using it to bring up a HIPAA-compliant private cloud.

Since Sector/Sphere is written in C++, it is straightforward to support C++ based data access tools and programming APIs.

If you have access to high speed research network (for example if you network can reach StarLight, the National Lambda Rail, ESNet, or Internet2), then you can try out the Sector Public Cloud.

You can reach the Sector Public Cloud from the Sector home page sector.sourceforge.net.

There is a technical report on the design of Sector on arXiv: arXiv:0809.1181v2.

There is some information on the performance of Sector/Sphere in my post on the MalStone Benchmark, a benchmark for clouds that support data intensive computing.