Should you follow the trend and migrate your data, workflows and infrastructure to GCP, AWS and Azure? During the Strata Data Conference in New-York, a general focus was put on moving customer’s Big Data solutions to the Cloud. Let’s see what has been addressed in each vendor’s talks, and what to consider before doing so.
This article was originally published by Adaltas and was written by Joris Rummens.
Context and Hype Cycles
Before diving into cloud vendors promises and their pitfalls, I’ll share the context on why this article was written.
Since Hortonworks and Cloudera’s merger, maybe even a little earlier, traditional on-premise Big Data is on a downhill trend. Companies started their lakes and analytic platforms and, around 2015, the hype was at the highest. Most of the actors realized the operational costs included with distributed technologies, and started searching for ways to alleviate them to focus on their core business instead.
Cloud services started their hype cycle as early as Big Data, but were at first primarily built for on-demand computing and simple highly available applications (eg. websites). While on-premise Big Data, especially Hadoop and Data Lakes, went to the “trough of disillusionment” stage mainly because of the aforementioned operational costs, Cloud providers started adding Big Data managed services to their catalog.
