Review of the `dm` package for R

DM allows you to bring a relational data model to R. It connects your collection of dataframes into a coherent representation of data. dm objects can be manipulated by dplyr/dbplry and dm also provides a set of tools to consume, create, and deploy relational data models. Like a relational database, there are methods for key creation, key selection, and field constraint checking. Data models built with dm can be ported to an RDBMS (*sql, posgres, etc). This means you can create a data model based on in memory data using familiar tools then you can put that data into an database so it can scale to billions of rows.

Visualize data models to help understand relationships
Joins based on known shared keys and a flatten operation that automatically follows keys to join tables and performs column name disambiguation
Constraint checking for fields
There is a single point of truth for data (they are normalized) so that updating a value in one place propagates across linked tables