If you’re new to Machine Learning or are in need of revamping your company’s ML infrastructure, you'll most likely end up in a similar situation to that of buying a car. You start the search for the best cars of 2020, safest or slickest. Jumping from one website to another but always watching your top priorities. So when you narrow it down to the last two options, it becomes a balancing game. With ML you also want to make sure the tools you choose provide the most benefits for the best value. In our case, we often get asked what’s the main difference between Datagran and other ML providers like Azure ML pipelines, Databricks, Datarobot, and Alteryx. So this article walks you through the differences between this group of tools for the sake of understanding the main differences between them and facilitate decision making.