Hadoop has been hamstrung by complexity, skills shortages and a lack of standardization, but new approaches to using Hadoop are emerging.
It’s been a decade since Hadoop became an Apache software project and released version 0.1.0. The open source project helped launch the Big Data era, created a foundation for most of the big cloud platform providers and changed how enterprises think about data.
Despite Hadoop’s rocket evolution from a Google pet project to a technology stack with major distributions and cloud providers, many enterprises still find Hadoop difficult, experts say. Rather than becoming simpler and easier, Hadoop spawned an entire ecosystem of open source tools and technologies, including Mesos, Spark, Hive, Kafta, Zookeeper, Phoenix, Oozie, HBase — all tied directly or indirectly to Hadoop.
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