No, I’m not describing the latest house for sale. (Although, I can appreciate the efficiencies that a new kitchen can bring to a classic home.) This is about technologies that have been relied on to process data for the last 30 to 50 years.
Mainframes, data warehouses (DW), and storage area networks (SAN) power mission-critical applications throughout the enterprise, by collecting, generating and processing large data volumes. Taking the case of a mainframe, many organizations would like to minimize the amount of data processed on their mainframes to defer upgrades and help reduce IT expenses as well as correlate mainframe operational data with other forms of data for analytical uses. Yet, companies face challenges when attempting to provide a reliable and seamless approach to augment mainframe or data warehouse workloads and data into Apache Hadoop as a way to modernize or optimize their data architecture with cost and capability advantages.
This is where the partnership between Syncsort and MapR is a natural fit. Announced at Hadoop Summit in early June, our partnership with Syncsort is already off to a great start with customers such as comScore, Experian, and others. It’s not a surprise that the Syncsort expertise in offloading data and processing workloads from traditional mainframes and data warehouses is a perfect match for our durable and highly available Hadoop distribution.
2014 marks the 50th anniversary for the mainframe. Data formats have changed tremendously since then and continue to grow in volumes, yet the mainframe is still in use by many of the world’s largest businesses and government agencies. The MapR partnership with Syncsort has the potential to help organizations cost-effectively build enterprise data architectures that optimize traditional platforms by offloading MIPS cycles, data storage, or COBOL programs easily into a modern, secure, and reliable Hadoop environment from MapR.
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