Spark Graduates Apache Incubator by Tiffany Trader.
From the post:
As we’ve touched on before, Hadoop was designed as a batch-oriented system, and its real-time capabilities are still emerging. Those eagerly awaiting this next evolution will be pleased to hear about the graduation of Apache Spark from the Apache Incubator. On Sunday, the Apache Spark Project committee unanimously voted to promote the fast data-processing tool out of the Apache Incubator.
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Databricks refers to Apache Spark as “a powerful open source processing engine for Hadoop data built around speed, ease of use, and sophisticated analytics.” The computing framework supports Java, Scala, and Python and comes with a set of more than 80 high-level operators baked-in.
Spark runs on top of existing Hadoop clusters and is being pitched as a “more general and powerful alternative to Hadoop’s MapReduce.” Spark promises performance gains up to 100 times faster than Hadoop MapReduce for in-memory datasets, and 10 times faster when running on disk.
BTW, the most recent release, 0.90, includes GraphX.