Ruby Object Mapper (ROM) is a fast ruby persistence library with the goal of providing powerful object mapping capabilities without limiting the full power of the underlying datastore.
More specifically, ROM exists to:
- Isolate the application from persistence details
- Provide minimum infrastructure for mapping and persistence
- Provide shared abstractions for lower-level components
- Provide simple use of power features offered by the datastore
Object hierarchies are very different from relational hierarchies. Relational hierarchies focus on data and its relationships whereas objects not only manage data, but also their identity and the behavior centered around that data. When attempting to reconcile those difference and map one to the other, we as developers end up splatting against a concrete wall.
We believe the cause can be attributed to a fundamental flaw behind ORMs; that is this idea that it's easy to:
Map objects to database tables one-to-one (the ActiveRecord design pattern); or
Introduce machinery to translate between objects and persistence structures (the DataMapper pattern)
Both strategies tend to start out fine, but can quickly become cumbersome as an application transitions to a medium-to-large application.
ActiveRecord style mapping has the benefit of aiding in rapid prototyping works great in basic CRUD scenarios but it limits application modeling to what's convenient for the database. Entities will tend to map one-to-one with tables, which leads to knowledge of the persistence structure infecting the application domain, leading to code that's difficult to change.
The DataMapper pattern, while one step better than ActiveRecord style mapping, still has its focus trained onto creating and managing objects. The pattern solves the one-to-one mapping issue but in doing so creates a host of others. The whole apparatus needed to manage all of those objects inevitably leads to performance issues and object state tracking which results in developers bypassing the ORM entirely.
The problems with ORMs are numerous and the above issues only begin to scratch the surface. If you're interested in further reading on the subject, we suggest:
ROM provides an alternative way of handling persistence and related concerns. It focuses on simplicity by providing enough abstractions to help you efficiently turn your raw data into meaningful information.
While many ORMs focus on objects and state tracking, ROM focuses on data and
transformations. Users of ROM implement
Relations, which give access to data.
Then using the relations you can associate them with other relations and query
the data using features offered by the datastore. Once raw data has been loaded,
it gets coerced into configured data types, and from there can be mapped into
whatever format is needed by the application domain, including plain ruby hashes,
convenient ROM Structs or custom objects.
The important concept above is that during the entire process there is no dirty tracking, no identity management and no mutable state. Just pure data being loaded and mapped as result of a direct request made from the application domain. Data can be persisted in ways that take advantage of the features provided by the datastore and the application domain can receive that data in any form it needs. Furthermore, you get the added benefits of:
- decoupling the application from the persistence layer without sacrificing flexibility, and
- bypassing the critical problems associated with object relational mapping and mutable state
Most likely, a decent percentage of developers will see the added abstractions as extraneous boilerplate. For those people we ask that you give ROM a chance, embrace its patterns and principles and see just how much easier it is to pull and transform your data. For those who have been burned by simple ORMs in the past, ROM represents a real, solid alternative.
ROM leverages Ruby’s linguistic strengths with a blend of Object Oriented and Functional styles. Following a powerful composition pattern, every ROM object shares a common pipeline interface and returns data without side-effects.
All ROM components are stand-alone; they are loosely coupled, can be used independently, and follow the single responsibility principle. A single object that handles coercion, state, persistence, validation, and all-important business logic rapidly becomes complex. Instead, ROM provides the infrastructure that allows you to easily create small, dedicated classes for handling each concern individually, and then ties them together in a developer-friendly ways.
Above all else ROM favors:
- Explicitness over "magic" whenever possible
- Speed, because performance is a feature
- Flexibility in your domain layer's design
Like ROM & its fundamental ideas? You should check these out, too:
- Rich Hickey on state, immutability, and how to leverage OO principles
- Gary Bernhardt on boundaries, immutability, and clean design
- Rich Hickey on the importance of simplicity for cognition
- Robert C. Martin (“Uncle Bob”) on hexagonal architecture
- Brad Urani on ActiveRecord vs. Ecto: A Tale of Two ORMs