Raff vs Railway: VM Control or Developer PaaS? (2026)

Introduction

Raff and Railway are not the same kind of cloud platform. Raff gives you direct control over virtual machines; Railway gives you a developer platform for shipping applications without thinking much about the server underneath.

That difference matters. If you are deploying a Node.js API, a small SaaS backend, or a prototype connected to GitHub, Railway can feel wonderfully fast. You push code, configure variables, and let the platform handle the deployment workflow. Railway is built around services, deployments, variables, environments, GitHub auto-deploys, health checks, scaling, regions, and related developer workflows.

Raff approaches the problem from the infrastructure side. A Raff Linux VPS gives you a server environment with full root access, KVM virtualization, SSH key authentication, Docker readiness, unmetered bandwidth, DDoS protection, firewall controls, and custom OS support. You control the machine, the operating system, the runtime, and the deployment pattern.

The practical question is not “Which platform is better?” The better question is:

Do you want VM control, or do you want a developer PaaS?

Raff Overview

Raff is a cloud infrastructure platform built around virtual machines, VPS hosting, storage, and developer-friendly infrastructure. With Raff, you choose a server, select the operating system, connect over SSH or RDP depending on the product, and configure the environment yourself.

That gives you control. You can install packages, change system services, run Docker, configure firewalls, host databases, run VPN software, deploy reverse proxies, or use the VM as a development, testing, or production server.

Raff is especially relevant when the workload is not just “deploy this web app.” A developer might use Raff to run Docker Compose, host PostgreSQL directly, deploy n8n, set up a private VPN, run a game server, operate a reverse proxy, or test a custom Linux environment.

Raff currently offers two main VM lines:

• CPU-Optimized starts at $3.99/month for 1 vCPU / 1 GB RAM / 25 GB NVMe SSD. It also includes 2 vCPU / 2 GB / 50 GB at $13.99/month, 2 vCPU HiMem / 4 GB / 80 GB at $19.99/month, 4 vCPU HiMem / 8 GB / 120 GB at $35.99/month, and 8 vCPU HiMem / 16 GB / 180 GB at $63.99/month.
• General Purpose starts at $5.99/month for 2 vCPU / 2 GB RAM / 40 GB NVMe SSD. The current 4 GB General Purpose tier is $9.99/month for 2 vCPU HiMem / 4 GB / 80 GB NVMe SSD.

Every VM plan is positioned around predictable infrastructure: unmetered bandwidth at 3 Gbps standard port speed, NVMe SSD storage, snapshots, automated backups, private networking, firewalls, DDoS protection, API/CLI workflows, and direct server access.

Railway Overview

Railway is a developer platform designed to simplify application deployment. Instead of asking you to manage a VM, Railway organizes your workload into services, deployments, variables, environments, volumes, and scaling settings.

Railway supports persistent services for long-running web apps, APIs, and workers; cron jobs for scheduled tasks; and functions for single-file TypeScript code. It also includes configuration concepts such as variables, environments, config-as-code, Dockerfiles, Railpack builds, GitHub auto-deploys, health checks, scaling, and regions.

That makes Railway appealing for teams that want to move quickly from repository to running application. Railway also has strong workflow features around environments, including isolated production, staging, development, and pull-request environments.

In short: Railway is designed to remove infrastructure friction. Raff is designed to give you infrastructure control.

Pricing Comparison

Raff and Railway use different pricing philosophies, so the comparison is not a simple “same server, different price” table.

Raff uses published VM tiers. You choose a VM size and know the baseline monthly cost before deploying. That makes Raff easier to budget for long-running servers, always-on services, self-hosted tools, Docker hosts, internal apps, databases, and workloads with predictable resource needs.

Railway uses a usage-based pricing model. The original article referenced Railway’s pricing page as listing a Free plan with trial credits, a Hobby plan with a minimum usage model and included monthly usage credits, and a Pro plan with a higher minimum usage model and included monthly usage credits. It also referenced usage rates for memory, CPU, volumes, egress, and object storage.

That distinction changes how you should think about cost.

With Raff, you generally ask:

• “What VM size do I need?”
• “How much CPU, RAM, and storage should I reserve?”
• “Do I want predictable monthly server cost?”
• “Do I want unmetered bandwidth included?”

With Railway, you generally ask:

• “How much CPU and memory will my app actually consume?”
• “How much egress will it generate?”
• “Will this workload be idle, bursty, or always-on?”
• “Will usage-based billing stay predictable for my team?”

Railway’s model can be attractive for apps that scale with demand or do not run heavily all the time. Raff’s model is often easier to reason about when you want a long-running server with predictable resources.

Raff VM pricing context

The old Raff General Purpose pricing should not be described as $4.99/month for 2 vCPU / 4 GB. The current General Purpose entry is $5.99/month for 2 vCPU / 2 GB, and the current 4 GB General Purpose plan is $9.99/month.

Feature Comparison

The biggest difference between Raff and Railway is the level of abstraction.

Raff gives you the server. Railway gives you the deployment workflow.

That affects nearly every decision: debugging, scaling, cost, observability, portability, security, and how much your team needs to know about Linux.

Compute and Runtime

Raff gives you virtual machines. You choose a Linux distribution, connect with SSH, and manage the operating system directly. This is the better model when you need root access, custom packages, long-running daemons, Docker Compose, custom networking, or server-level control.

Railway gives you services. A service might be a web app, an API, a background worker, a cron job, or a function. You are not usually thinking about the OS as the main unit. You are thinking about the app, build, deployment, variables, environment, and scaling configuration.

Choose Raff if the operating system matters. Choose Railway if the application workflow matters more than the server.

Deployment Workflow

Railway is stronger when your ideal workflow starts with a Git repository. It supports GitHub-connected deployments, Docker image deployment, local repo deployment through CLI workflows, preview environments, build/deploy logs, metrics, and related developer workflow features.

Raff is more flexible, but less automatic by default. You can deploy anything, but you are responsible for deciding how to deploy it. That might mean SSH, Git pull, Docker Compose, CI/CD, Ansible, Terraform, or a custom script.

This is a trade-off. Railway removes steps. Raff removes platform limits.

Variables and Configuration

Railway has a strong built-in variables system. Railway variables can be used during build, deployment, local commands, and environment-based workflows. It supports service variables, shared variables, reference variables, and sealed variables for sensitive values.

On Raff, environment variables are usually configured through the OS, your shell, your process manager, Docker Compose, systemd, a .env file, or your deployment tool. This gives you more control, but you must choose the pattern yourself.

Railway is more convenient here. Raff is more transparent and portable.

Scaling

Railway includes platform-level scaling features. Its docs describe vertical scaling, horizontal scaling with replicas, multi-region replicas, and built-in load-balancing behavior between replicas.

Raff scaling is VM-oriented. You resize the VM, add more VMs, configure a load balancer or reverse proxy, move databases to separate servers, or design your own architecture. That requires more operational knowledge, but it also gives you direct control over how the system is built.

Railway scaling is convenient. Raff scaling is architectural.

Storage and Persistent Workloads

Raff is a natural fit for persistent server workloads because you control the VM and disk environment. Raff supports NVMe SSD-backed VM storage, snapshots, automated backups, block storage volumes, and S3-compatible object storage.

Raff includes the first three automated backups per VM. Additional backup and snapshot storage should be checked against Raff’s current pricing page before publication.

Railway also supports storage through volumes and object storage pricing, but its core mental model is still service-centric. If you want to manage a database, file server, Docker volume, or persistent application state directly, Raff’s VM model is easier to reason about. If you want platform-managed service deployment with attached volumes, Railway’s model can be faster.

Bandwidth and Egress

This is one of Raff’s clearest advantages for long-running workloads.

Raff VM plans include unmetered bandwidth at 3 Gbps standard port speed. That makes it easier to run APIs, downloads, web apps, customer-facing services, and self-hosted tools without constantly modeling egress.

Railway uses usage-based egress pricing. That can work well for small apps or early-stage deployments, but it can become harder to forecast as traffic grows.

If traffic is unpredictable or customer-facing, Raff is easier to budget. If the app is low-traffic, idle, or bursty, Railway’s usage model can be efficient.

Who Should Choose Raff?

Choose Raff if you want control over the server.

Raff is the better fit when you need:

• Full root access
• SSH-based administration
• Custom Linux configuration
• Docker, Docker Compose, or k3s
• Databases and caches you manage yourself
• Reverse proxies, VPNs, or game servers
• Predictable VM-style pricing
• Unmetered bandwidth
• Long-running workloads that should not depend on a PaaS abstraction

Raff is also a strong fit for developers who are learning infrastructure. If you want to understand Linux, networking, firewalls, processes, logs, and deployment fundamentals, a real VM teaches you more than a highly abstracted PaaS.

There is a cost angle as well. Usage-based PaaS pricing can be efficient, but it can also surprise teams when an always-on service grows in CPU, memory, egress, or storage. Raff’s fixed VM model makes the baseline easier to forecast.

Who Should Choose Railway?

Choose Railway if you want deployment speed over server control.

Railway is the better fit when you need:

• GitHub-connected deployments
• Fast app launches
• Built-in variables and secrets workflows
• Preview environments for pull requests
• Service-based scaling
• Less Linux administration
• A Heroku-like developer experience with modern tooling

Railway is especially appealing for small teams shipping web apps, APIs, workers, and prototypes. If your main goal is “push code and get a running service,” Railway is designed around exactly that workflow.

Railway also gives teams useful collaboration and workflow patterns. Its environment model supports isolated production, staging, development, and PR environments, which can be valuable for teams that review changes frequently.

Migration Considerations

Migrating from Railway to Raff is less about copying a VM and more about recreating the runtime.

A typical migration looks like this:

1. Create a Raff Linux VM.
2. Install the runtime: Node.js, Python, Go, Docker, PostgreSQL, Redis, or whatever your app needs.
3. Copy the application code or container image.
4. Recreate Railway variables as .env files, systemd environment files, Docker Compose variables, or CI/CD secrets.
5. Move persistent data from Railway volumes or databases.
6. Configure Nginx, Caddy, Traefik, or another reverse proxy.
7. Update DNS.
8. Monitor logs, CPU, RAM, disk, and network usage.

Moving from Raff to Railway is the opposite process. You take an app currently running on a VM and adapt it to Railway’s service model. That may be easy for a twelve-factor web app, but harder for workloads that depend on custom system packages, daemons, low-level networking, or multiple processes sharing the same machine.

Conclusion

Raff and Railway are both useful, but they optimize for different kinds of developers.

Railway is for teams that want to deploy application services quickly with less infrastructure management. It shines when your workflow is Git-based, your app fits the PaaS model, and you value built-in environments, variables, preview deployments, and platform-level scaling.

Raff is for developers and teams that want direct infrastructure control. It shines when you need root access, predictable VM pricing, custom Linux configuration, Docker flexibility, persistent workloads, unmetered bandwidth, or the ability to run software that does not fit neatly into a PaaS service box.

The simplest way to decide is this:

Choose Railway if you want to deploy an app. Choose Raff if you want to control the machine that runs it.

For developers who want to understand and own their infrastructure, start with a Raff Linux VM. For teams that need predictable long-running compute, compare Raff’s current CPU-Optimized and General Purpose VM plans before choosing a deployment model.