Apache Sqoop(TM) is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
MRQL (the Map-Reduce Query Language) is an SQL-like query language for map-reduce computations. It is implemented on top of Apache's Hadoop. MRQL is powerful enough to express most common data analysis tasks over many different kinds of raw data, including hierarchical data and nested collections, such as XML data. It is more powerful than other current languages, such as Hive and Pig Latin, since it can operate on more complex data and supports more powerful query constructs, thus eliminating the need for using explicit map-reduce code.
Hama is a distributed computing framework based on BSP (Bulk Synchronous Parallel) computing techniques for massive scientific computations (e.g., matrix, graph, network, ..., etc), Currently being incubated as one of the incubator project by the Apache Software Foundation.
Spark is a fast, in-memory cluster computing framework with a language-integrated interface in Scala. It shines at iterative MapReduce (e.g. machine learning) and interactive data mining, where keeping data in memory provides substantial speedups.