By the end of the first decade, we needed a fundamental rethink — not just for the public cloud, but also for on-premises. It’s also helpful to cast an eye on the various technological forces driving Hadoop’s evolution over the next decade:
– Cloud experiences fundamentally changed expectations for easy to use, self-service, on-demand, elastic consumption of software and apps as services.
– Separation of compute and storage is now practical in both public and private clouds, significantly increasing workload performance.
– Containers and kubernetes are ubiquitous as a standard operating environment that is more flexible and agile.
– The integration of streaming, analytics and machine learning — the data lifecycle — is recognized as a prerequisite for nearly every data-driven business use case.
“Core” Hadoop (not including products in the broader Hadoop ecosystem like Spark, Kafka, etc.) hit a major stress point with migration out of data centers running direct attached storage. This is how Cloudera is working to pick up some of that lost momentum.