SAP inks Hadoop deals with Intel and Hortonworks
The announcement was made on Wednesday at Techcrunch Disrupt in San Francisco, and means SAP will be able to sell SAP’s HANA in-memory database alongside the two Apache Hadoop distributions from Intel and Yahoo!-spinout Hortonworks.
The tie-up is part of an “expanded big data” strategy by SAP, according to a canned statement, that will also see it take a “big data bus” stuffed with computers running analytical applications around North America as it seeks to educate customers about big data.
The deal sees SAP adopt two different flavors of Hadoop: one that is a tweaked proprietary distribution (Intel’s), and another that is entirely open (Hortonworks’).
“With performance optimizations for Intel hardware as well as encryption and decryption improvements for better security, the integration of the Intel Distribution for Apache Hadoop with the SAP HANA platform provides enterprises with security and scalability,” Intel’s datacenter software division general manager Boyd Davis said.
On the other hand, Hortonworks CEO Rob Bearden told The Register, “In our world, everything we do and build is in the common Apache [Hadoop] trunk.”
By reselling the two Hadoop distros, large SAP customers can have a combined vendor for their analytics and data platform products, and it means longtime SAP customers can likely get the software wrapped in with their ongoing contracts.
The news follows SAP’s February announcement that it plans to combine the Intel Distribution for Apache Hadoop with its HANA platform.
“Integration with Apache Hadoop is part of SAP’s overall strategy to provide valuable insights across a continuum of data from the efficient storage of massive amounts of cold data, to petabyte-level storage of warm data to real-time and streaming data analysis,” SAP said in a statement.
The adoption of Hadoop by SAP marks yet another instance of a software-specialist vendor trying to gain a footprint in the burgeoning data platform, and follows similar close moves by IBM, Microsoft, Oracle, and others. By Jack Clark Source