Where change is welcome.
We are excited to announce the immediate availability of StreamSets DataOps Platform SDK for Python version 4.0.0. It enables users to interact with StreamSets DataOps Platform programmatically using Python 3.4+. Highlights of the StreamSets SDK SDK Activation key is no…
Migrating from an on-premises data lake to a cloud data lake does not have to take months or even weeks. With intent-driven data pipelines, you can migrate your data from Hadoop to a cloud data lake in hours. In this…
‘Simplicity is the ultimate sophistication.’
– Leonardo da Vinci
As a recent hire on the Engineering Productivity team here at StreamSets, my early days at the company were marked by efforts to dive head-first into StreamSets Data Collector (SDC), a fast data ingestion engine, to build data pipelines. As it turns out, the Docker images we publish for SDC were the easiest way to explore its vast set of features and capabilities, which is exactly why I am writing this blog post.
Without further ado, let’s get started.