UPDATED 09:34 EDT / SEPTEMBER 27 2013

Hortonworks and WANdisco Expand Partnership with Non-Stop Hadoop Integration

Hortonworks and active-active replication provider WANdisco announced today that they have expanded their partnership in an effort to establish Hadoop as a viable data platform for the enterprise. Under the agreement, Hortonworks will update its open source Hadoop distribution to support WANdisco’s Non-Stop technology, a network solution that eliminates the single point of failure in HDFS by synchronizing all NameNodes in a cluster.

WANdisco joined the the Big Data startup’s partner program earlier this year to package its analytics solutions with the increasingly popular Hortonworks Data Platform, or HDP. The distribution is used by more than 100 customers, including music streaming provider Spotify.

“Enterprises are increasingly adopting Apache Hadoop as a core element of their IT infrastructure,” said David Richards, the chairman and chief executive officer of WANdisco. He explained that “working with Hortonworks is a natural fit given their leadership in the Apache Hadoop community. A major enterprise requirement is continuous data availability and WANdisco’s Non-Stop Hadoop Technology is the only technology available that addresses it. The combination of WANdisco, Hortonworks and SAP will provide a reference architecture for Hadoop in the Enterprise.”

Partnerships are central to WANdisco’s plans for popularizing its technology. A few weeks ago the company revealed that Non-Stop NameNode WAN Edition has been certified for integration and interoperability with Dell PowerEdge servers. Shortly afterwards, Hortonworks announced that it has partnered with SAP to make its distribution available for the BI’s giant enterprise customers.

Prior to joining forces with SAP, the analytics startup allied with Microsoft to make HDP available for Windows Server 2008 R2 and Windows Server 2012. As the first Hadoop distributor to get its offering certified for Windows, Hortonworks has a head start over rivals Cloudera and MapR.


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