SAP has signed deals with Intel and Hortonworks to resell Intel’s Apache Hadoop distribution and Hortonworks Data Platform. Under the terms of the agreements, SAP will integrate those Hadoop products with its own HANA in-memory technology. By supporting Hadoop in conjunction with its other products, including BusinessObjects and SAP Sybase IQ Software, SAP is attempting to mine Hadoop’s current popularity among developers and businesses with massive amounts of unstructured data to crunch. While that popularity will likely endure for some time—research firm IDC has estimated that the Hadoop market could hit $812.8 million by 2016, and that’s considered a conservative number—the bigger question is whether all the tech companies rushing into the Hadoop space can actually profit from that interest. Certainly a number of distributions and associated software platforms will survive; but for every Hadoop-based tool that gains traction with businesses, another four or five will end up consigned to history’s dustbin of dead tech. The open-source nature of Apache Hadoop could further complicate things for companies seeking to make a buck off the framework. “The Hadoop and MapReduce market will likely develop along the lines established by the development of the Linux ecosystem,” Dan Vesset, vice president of Business Analytics Solutions for IDC, wrote in a statement last year. “Over the next decade, much of the revenue will be accrued by hardware, applications, and application development and deployment software vendors.” Intel claims its Hadoop distribution is built to exploit underlying hardware to analyze data at speeds superior to other distributions on the market—namely, one terabyte of data every seven minutes, versus the hours delivered by other systems. In turn, SAP also claims its HANA in-memory technology will accelerate complicated data projects. Combine the two, and (at least in theory), you have a platform capable of tearing through massive amounts of unstructured data. But it remains to be seen how well such a mixed bucket of products will work together in real-world scenarios. Image: seewhatmitchsee/Shutterstock.com SAP Deals Show Hadoop Still Going Strong
SAP has signed deals with Intel and Hortonworks to resell Intel’s Apache Hadoop distribution and Hortonworks Data Platform. Under the terms of the agreements, SAP will integrate those Hadoop products with its own HANA in-memory technology. By supporting Hadoop in conjunction with its other products, including BusinessObjects and SAP Sybase IQ Software, SAP is attempting to mine Hadoop’s current popularity among developers and businesses with massive amounts of unstructured data to crunch. While that popularity will likely endure for some time—research firm IDC has estimated that the Hadoop market could hit $812.8 million by 2016, and that’s considered a conservative number—the bigger question is whether all the tech companies rushing into the Hadoop space can actually profit from that interest. Certainly a number of distributions and associated software platforms will survive; but for every Hadoop-based tool that gains traction with businesses, another four or five will end up consigned to history’s dustbin of dead tech. The open-source nature of Apache Hadoop could further complicate things for companies seeking to make a buck off the framework. “The Hadoop and MapReduce market will likely develop along the lines established by the development of the Linux ecosystem,” Dan Vesset, vice president of Business Analytics Solutions for IDC, wrote in a statement last year. “Over the next decade, much of the revenue will be accrued by hardware, applications, and application development and deployment software vendors.” Intel claims its Hadoop distribution is built to exploit underlying hardware to analyze data at speeds superior to other distributions on the market—namely, one terabyte of data every seven minutes, versus the hours delivered by other systems. In turn, SAP also claims its HANA in-memory technology will accelerate complicated data projects. Combine the two, and (at least in theory), you have a platform capable of tearing through massive amounts of unstructured data. But it remains to be seen how well such a mixed bucket of products will work together in real-world scenarios. Image: seewhatmitchsee/Shutterstock.com 
