In some ways Hortonworks is old fashioned in that it still clings to the stretch goal of managing half of the world’s data in an era where cloud object stores and bespoke analytic services are adding more alternatives to the mix. Hortonworks’ aspirational goal may not be realistic, but never mind, there are bigger fish to fry. The underlying message from this year’s North American DataWorks Summit and analyst briefings is that the company is competing and facing the challenges of navigating a multipolar cloud world.
My big on data bro Andrew Brust reported the headlines coming out earlier in the week: Hortonworks is releasing the 3.0 version of its data platform that, confusingly, is based on Hadoop 3.1. As we reported back at the start of the year, the 3.x generation of Apache Hadoop will mark a watershed with containerization and storage. HDP 3.0 adds YARN support for running Docker containers, meaning you can run containerized jobs with all dependencies and configurations rolled in. It also supports erasure coding, providing a path to tiering data, and begins abstracting support for specialized hardware such as GPUs.
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