The Modern Data Stack is a set of tools and best practices that enables analytics engineers to rigorously develop data models that facilitate analysis, reporting, and other operational use cases. In contrast, a Modern ML Stack has not emerged to support the development of ML-driven products and applications. In this post, Ethan Rosenthal argues that MLOps could be streamlined and simplified if companies used existing databases and data management systems for use cases like model monitoring and feature engineering.