MOA (Massive On-line Analysis) is a framework for data stream mining. It includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, it is also written in Java, while scaling to more demanding problems. The goal of MOA is a benchmark framework for running experiments in the data stream mining context by providing

• storable settings for data streams (real and synthetic) for repeatable experiments,
• a set of existing algorithms and measures form the literature for comparison and
• an easily extendable framework for new streams, algorithms and evaluation methods.

More details can be found on the MOA project homepage.