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What is Trailblazer?

Trailblazer is a thin layer on top of Rails. It gently enforces encapsulation, an intuitive code structure and gives you an object-oriented architecture. In a nutshell: Trailblazer makes you write logicless models that purely act as data objects, don't contain callbacks, nested attributes, validations or domain logic. It removes bulky controllers and strong_parameters by supplying additional layers to hold that code and completely replaces helpers.
Trailblazer is a tool in the Frameworks (Full Stack) category of a tech stack.
Trailblazer is an open source tool with 3.2K GitHub stars and 140 GitHub forks. Here’s a link to Trailblazer's open source repository on GitHub

Who uses Trailblazer?


14 developers on StackShare have stated that they use Trailblazer.

Trailblazer Integrations

Pros of Trailblazer
Trailblazer allows creating sane, large apps in Rails
Separates business logic from framework
Sound Software Architecture principals
Improves maintainability
Makes Rails better

Trailblazer Alternatives & Comparisons

What are some alternatives to Trailblazer?
Share data effortlessly with your team
Originally built at Lyft, Envoy is a high performance C++ distributed proxy designed for single services and applications, as well as a communication bus and “universal data plane” designed for large microservice “service mesh” architectures.
Pathfinder is a new real-time routing service in public beta. Pathfinder calculates routes for transportation services. These routes are updated in real time as users make transportation or delivery requests. Through our SDKs, applications can subscribe to routes as they change in response to user requests.
It helps you understand and explore advanced deep learning. It is actively used and maintained in the Google Brain team. You can use It either as a library from your own python scripts and notebooks or as a binary from the shell, which can be more convenient for training large models. It includes a number of deep learning models (ResNet, Transformer, RNNs, ...) and has bindings to a large number of deep learning datasets, including Tensor2Tensor and TensorFlow datasets. It runs without any changes on CPUs, GPUs and TPUs.
Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
See all alternatives

Trailblazer's Followers
23 developers follow Trailblazer to keep up with related blogs and decisions.