Consumable Big Data : Cloudera repackages + adds Spark support
Cloudera this week delivered on its October promise to provide a centralized enterprise analytics platform with a major portfolio overhaul that introduces three new offerings and support for the fast-growing Apache Spark project. Hailed as the next big thing in Big Data by SiliconANGLE founding CEO John Furrier, the framework executes queries up to 100 times faster than MapReduce and enables in-memory stream processing.
The first and most important addition to the company’s lineup is Cloudera Enterprise Data Hub Edition, which packages its open source Hadoop distribution with a set of “advanced components” that consists of HBase, Spark, the Impala structured query engine and homegrown search and auditing tools. The bundle also includes across-the-board, and closes the circle on a remark Cloudera co-founder and CTO Amr Adwallah made on theCUBE last year.
“The way we look at this is there’s an existing market called the EDW market, the enterprise data warehouse market. We’re saying now there’s a new market called the enterprise data hub (EDH) market. So there’s EDW and EDH. Us, Cloudera, being the very first leaders of this movement, we are naming that, that is the name of our market,” the executive told Furrier and Wikibon co-founder Dave Vellante in an exclusive interview at SiliconANGLE’s Big Data NYC event (watch the entire segment below).
Customers that don’t need the whole package can opt to go with the Enterprise Flex Edition, a slimmed down version of the offering that comes with only one advanced component of their choosing. For the most economic minded organizations, Cloudera is offering a Basic Edition that features only the core Hadoop distro plus support.
The firm says that the three editions are better aligned with the most common use cases for the batch processing framework, enabling companies of different sizes to analyze their unstructured data within budget.
photo credit: Social BIz Solutions via photopin cc
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