What is the difference between Apache Mahout and PredictionIO?

What are the differences in their usage and the main reason for development of PredictionIO?

Solution

From wikipedia:

Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification

From predictionio website:

PredictionIO is an open source Machine Learning Server built on top of state-of-the-art open source stack for developers and data scientists create predictive engines for any machine learning task. It is as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Spray and Elasticsearch, which simplifies and accelerates scalable machine learning infrastructure management.

Apache Mahout is used to implement machine learning algorithms in a hadoop-based environment.

Predictionio is a full tech stack used to bring machine learning to a production environment. With predictionio, you can more easily build, train, deploy algorithms. It comes with an http server and database backend. PredictionIO actually used to be built on top of Apache Mahout but switched to Apache Spark.