Railway deploys easily, but your data stays in the US

Railway is popular for backend developers. Connect a repo, get a database, deploy. But Railway is a US company on US infrastructure. If you're a Canadian team handling real data, that matters.

The jurisdiction reality

Railway runs on its own bare metal infrastructure across four regions: US West (California), US East (Virginia), EU West (Amsterdam), and Southeast Asia (Singapore). There is no Canadian region. Railway itself is a San Francisco-based US company, which means it's subject to the CLOUD Act regardless of where the data physically sits. Your API requests, database connections, and logs all flow through US systems.

Even if you deploy to their EU West region, Railway is still a US company. The CLOUD Act follows the company, not the data center. A US court can compel Railway to produce your data whether it sits in Oregon or Amsterdam. For Canadian teams, this means your data is governed by US legal process no matter which Railway region you choose.

For side projects and internal tools, this doesn't matter. But if clients ask "where is our data?" then "US infrastructure, US company" may not work.

The backend data problem

Frontend hosting has an escape hatch: static sites don't store data. Backend services don't have that luxury. Your API endpoints receive user data. Your databases store it. Your logs capture it. With Railway, all of this lives on US infrastructure, stored by a US company.

Consider the kinds of applications Canadian teams build on platforms like Railway. A healthcare startup handling patient intake forms. A legal tech company processing case documents. A B2B SaaS product where enterprise clients sign data residency clauses before onboarding. A fintech app that stores KYC documents and transaction records. In each case, the backend is the part that touches sensitive data, and the backend is where jurisdiction matters most.

It's not just regulated industries. Any SaaS product that stores client data will eventually face the question. A mid-size agency builds a client portal on Railway. Six months later, a prospective client sends over a security questionnaire asking where data is stored and which jurisdiction governs it. "US bare metal, US company" is a factual answer that may cost you the deal.

If you have data residency requirements in contracts, or just don't want your infrastructure under US law, Railway can't help.

Railway's pricing model

Railway uses per-resource usage-based pricing. You pay a base subscription ($5 USD/month for Hobby, $20 USD/month for Pro) that includes an equivalent amount of resource credits. After that, you pay for what you use: roughly $20 USD per vCPU per month, $10 USD per GB of RAM per month, about $0.15 per GB of disk storage, and $0.05 per GB of egress.

This model works well for small projects with predictable, low resource usage. If your app barely touches its allocation, you pay only the base subscription. But backend services tend to grow. Add a PostgreSQL database, a Redis cache, a background worker, and a web server, and the per-resource charges stack up. A typical backend with a database can easily run $40-80 USD per month, and that's before traffic spikes.

The challenge is predictability. With usage-based pricing, your bill changes month to month. A marketing campaign that drives a traffic spike, a client importing a large dataset, a background job that runs longer than expected. Each of these shows up on your invoice. For teams that need to forecast infrastructure costs or commit to a monthly budget, this creates friction.

MapleDeploy uses flat pricing instead. The Starter plan is $45 CAD/month for a dedicated VM with 4 GB RAM, 2 vCPUs, and 35 GB storage. Deploy as many services and databases as you want within those resources. No per-project fees, no egress charges, no surprises. You know exactly what you'll pay before the month starts.

Railway's database story

Railway offers one-click templates for PostgreSQL, MySQL, Redis, and MongoDB. The setup experience is genuinely good. Click a template, get a connection string, connect your app. No configuration files, no provisioning delays.

The tradeoff is that those databases run as containers on Railway's shared infrastructure, billed per resource. Your PostgreSQL instance consumes RAM and CPU that count against your usage. If your database grows, so does your bill. And all of it runs on US infrastructure, which means your stored data is subject to US jurisdiction.

With MapleDeploy, you get a full Coolify instance on a dedicated VM. Coolify supports one-click deployment of PostgreSQL, MySQL, Redis, MongoDB, and dozens of other services. The difference is that those databases run on your own VM in Toronto, on Canadian infrastructure, with resources that are yours regardless of how much or how little you use them.

Migrating from Railway

Moving off Railway is more straightforward than it might seem. Railway deploys from Docker or from a git repo using a Dockerfile or its zero-config builder (Railpack, which replaced Nixpacks). If your app runs on Railway, it almost certainly runs on any Docker-compatible platform.

The migration path looks like this. Export your database using pg_dump (for PostgreSQL) or the equivalent for your database engine. Set up your services on MapleDeploy through Coolify's interface, which supports the same git-based deploy workflow. Import your database dump. Update your DNS records. The core application code doesn't change because Railway doesn't lock you into proprietary APIs for basic deployment.

The one area that takes more thought is Railway's environment variable and service linking system. Railway auto-injects connection strings between services. On Coolify, you configure these explicitly through the dashboard. It's a few extra minutes of setup, but it means you can see and control every connection string rather than relying on platform magic.

If you're using Railway templates for common stacks (Next.js + PostgreSQL, Django + Redis), Coolify has equivalent one-click templates. The workflow is similar: pick a template, connect your repo, deploy.

The Canadian alternative

A Railway equivalent with Canadian jurisdiction needs: managed databases, git-based deploys, and servers physically in Canada operated by a Canadian company. See our full Railway comparison for a side-by-side breakdown.

MapleDeploy offers the same workflow (git push deploys, one-click databases, real-time logs) on Canadian infrastructure. Every customer gets a dedicated VM in Toronto. No shared containers, no noisy neighbors, no US jurisdiction over your data.

The underlying platform is Coolify, an open-source deployment tool that provides the same developer experience Railway is known for. Git push triggers a build and deploy. Databases spin up in one click. Logs stream in real time. The difference is that it all runs on your own infrastructure in Canada, and you can see exactly how the platform works because the code is open source.

For a step-by-step walkthrough, see our getting started guide. We also cover our full infrastructure stack and payment processing tradeoffs in dedicated posts.