Railway vs AWS for Solo Developers

Comparing Railway and AWS for solo developers. Features, pricing, pros and cons, and which one to pick for your next project.

Quick Comparison

Feature	Railway	AWS
Type	Managed app platform	Full cloud infrastructure (200+ services)
Entry plan	Hobby $5/mo, includes $5 of usage	Pay-as-you-go; new-account free plan gives up to $200 in credits for 6 months
Compute rate	$20 per vCPU/mo, $10 per GB RAM/mo, billed per second	EC2 t4g.small (2 vCPU, 2 GiB) about $0.0168/hr, roughly $12.24/mo on-demand
Egress	$0.05 per GB	$0.09 per GB to internet, first 10 TB tier; first 100 GB/mo free
Learning Curve	Easy	Hard
Best For	Quick full-stack deploys	Enterprise-scale infrastructure
Solo Dev Rating	8/10	5/10

Railway Overview

Railway makes backend deployment feel like it should have always been this easy. Connect a Git repo, Railway detects your framework, and your app is running. Add Postgres, Redis, or any other service from the dashboard. Environment variables are shared between services automatically. The visual canvas shows how your services connect. Logs stream in real time.

I use Railway when I want a backend running without spending time on infrastructure. The whole process from repo to production takes less than 10 minutes. The usage-based pricing means I'm not paying for idle resources during development. And the deploy experience is consistent whether I'm running Node, Python, Go, or a custom Dockerfile.

Railway's limitations show at scale. Resource limits, limited region selection, and less granular control over networking and security compared to raw infrastructure. For solo developer projects, these rarely matter.

AWS Overview

AWS is the dominant cloud platform with over 200 services covering every conceivable infrastructure need. EC2 for compute, RDS for managed databases, S3 for storage, Lambda for serverless, ECS/EKS for containers, SQS for queues, CloudFront for CDN. If you can imagine the infrastructure, AWS has a service for it.

I'll be direct. AWS is not designed for solo developers. It's designed for teams of cloud engineers managing enterprise workloads. The console is overwhelming, the documentation is encyclopedic, and the pricing model requires a calculator to understand. I've personally spent more time debugging IAM permissions than actually building features on projects where I used AWS.

The old 12-month free tier used to give you a generous taste of the platform without cost, but AWS changed the model on July 15, 2025. New accounts now sign up to a free plan that grants $100 in credits immediately plus up to $100 more for completing onboarding tasks, capped at $200 total, and the free plan closes after six months or when the credits run out, whichever comes first. The classic 12-month allowances (750 hours of t2.micro or t3.micro EC2, 750 hours of db.t3.micro RDS, and so on) now apply only to accounts created before that date. Whichever plan you land on, billing surprises are common once the credits are gone. A misconfigured NAT gateway, a forgotten EC2 instance, an unexpectedly large S3 bill. These are real risks for solo developers who don't monitor their AWS spending daily.

Key Differences

Complexity. This is the fundamental divide. Deploying a backend with Postgres on Railway takes 10 minutes and requires no infrastructure knowledge. The equivalent on AWS involves EC2 or ECS for compute, RDS for the database, VPC for networking, security groups for firewall rules, IAM for permissions, and Route 53 for DNS. That's 6+ services to configure for a basic backend.

Time to production. Railway gets you from zero to deployed in minutes. AWS gets you from zero to deployed in hours or days, depending on your familiarity with the platform. For solo developers shipping products, this time difference is significant.

Control and flexibility. AWS gives you granular control over every aspect of your infrastructure. Network topology, instance types, auto-scaling rules, IAM policies, custom VPCs. Railway abstracts all of this away. If you need specific infrastructure configurations, AWS provides them. If you don't, Railway saves you from having to think about them.

Pricing predictability. Railway's usage-based pricing is straightforward. You can estimate your monthly bill by looking at your resource consumption in the dashboard. AWS pricing involves per-service rates that vary by region, request count, data transfer direction, instance type, and billing mode (on-demand vs reserved vs spot). Solo developers regularly get caught by unexpected AWS charges.

Ecosystem breadth. AWS has services for machine learning, IoT, media transcoding, game server hosting, satellite communication, and hundreds of other specialized use cases. Railway handles web services, databases, and background workers. If your project needs something exotic, AWS probably has a managed service for it. Railway doesn't compete in these niches.

Vendor lock-in. Railway has minimal lock-in. Your app is a Docker container or a standard runtime app. Move to any other platform easily. AWS services like DynamoDB, SQS, Lambda, and Step Functions create deep lock-in. Once your architecture relies on AWS-specific services, migrating is a substantial project.

By the Numbers (2026)

Numbers checked on 2026-05-29. See the Sources list for every figure.

Railway

Plans: Hobby is $5 per month and includes $5 of resource usage. Pro is $20 per month per seat and includes $20 of usage. A one-time $5 trial credit lets you try it with no card.
Resource rates: $20 per vCPU per month, $10 per GB of RAM per month, $0.05 per GB of network egress, and $0.15 per GB per month for volume storage. Billing is metered per second of actual use.
CLI: version 4.65.0, published 2026-05-27. The @railway/cli npm package pulled 182,479 downloads in the week of 2026-05-21 to 2026-05-27. The railwayapp/cli repo sits at 549 GitHub stars.

AWS

Free tier: as of July 15, 2025, new accounts get $100 in credits up front plus up to $100 more for onboarding tasks, $200 maximum, and the free plan ends after six months or when credits run out. Legacy 12-month allowances only apply to accounts opened before that date.
Sample on-demand compute (us-east-1): EC2 t4g.small (2 vCPU, 2 GiB) is about $0.0168 per hour, roughly $12.24 per month run continuously. The smaller t4g.micro (2 vCPU, 1 GiB) is about $0.0084 per hour. RDS db.t4g.micro for PostgreSQL (2 vCPU, 1 GiB) is about $0.016 per hour, roughly $11.52 per month.
S3: $0.023 per GB per month for Standard storage, first 50 TB tier. Data transfer out to the internet is $0.09 per GB for the first 10 TB each month, with the first 100 GB per month free across all services.
Tooling adoption: the aws/aws-cdk repo has 12,785 GitHub stars and the aws/aws-cli repo has 16,997. On npm, aws-cdk-lib saw 3,463,294 downloads in the week of 2026-05-21 to 2026-05-27. AWS clearly has the larger tooling ecosystem; that breadth is exactly what makes the learning curve steep.

Real Cost at Solo-Dev Scale

Here is a like-for-like estimate for a small full-stack app, the kind a solo developer actually ships. Assume one always-on web service using 1 vCPU and 1 GB of RAM, a small Postgres database, about 10 GB of volume or object storage, and 50 GB of outbound traffic a month. All rates below are the real per-unit figures from the sources at the end, computed by hand.

Railway (Hobby plan)

Compute: 1 vCPU at $20 plus 1 GB RAM at $10 equals about $30 per month if the service truly runs at full allocation around the clock. Real apps idle below their ceiling because billing is per second of use, so the practical figure is usually lower.
Storage: 10 GB at $0.15 per GB equals $1.50.
Egress: 50 GB at $0.05 per GB equals $2.50.
The $5 Hobby fee already includes $5 of that usage, so you are billed the overage. Rough all-in: about $30 to $34 per month at full utilization, and meaningfully less when the service is idle.

AWS (after free credits are gone, us-east-1, on-demand)

Compute: one t4g.small EC2 instance running all month is about $12.24. A db.t4g.micro Postgres instance is about $11.52.
Storage: 10 GB of S3 Standard at $0.023 per GB is about $0.23, and EBS or RDS storage adds a few dollars more.
Egress: 50 GB out, minus the first 100 GB free, lands at $0 for this size of workload. Egress only starts to bite past the free allowance.
Rough all-in: about $24 to $30 per month, before you count the NAT gateway, load balancer, or data transfer between availability zones that a "real" production setup usually pulls in. Those add-ons are where AWS bills quietly balloon.

The headline numbers land close at this scale. The honest difference is not the sticker price, it is the failure mode. On Railway the worst case is your usage meter ticking up a few dollars. On AWS the worst case is a forgotten resource, a misread egress tier, or a NAT gateway you never noticed, any of which can turn a $25 month into a $200 month. For a solo developer without a billing alarm habit, that asymmetry matters more than the base rate.

When to Choose Railway

You want a backend running in minutes, not hours
Your project is a standard web app with a database and optional background workers
Predictable, straightforward pricing matters to you
You'd rather build features than configure infrastructure
You're a solo developer without a dedicated DevOps person

When to Choose AWS

Your project needs specific services that only AWS provides (SageMaker, SQS, DynamoDB)
You're building for enterprise clients who require AWS compliance certifications
You want to invest in cloud infrastructure skills for your career
Your application has complex scaling requirements with specific instance types
You've outgrown managed platforms and need granular infrastructure control

The Verdict

For solo developers building web applications, Railway is the better choice. The deploy experience is faster, the pricing is simpler, and you avoid the operational overhead of managing AWS infrastructure. The time you save not configuring VPCs and IAM policies is time you can spend building your product.

AWS makes sense when you have genuinely complex infrastructure needs or when you're building for clients who require it. Enterprise compliance, specialized AI/ML services, or multi-region architectures with specific failover requirements. These are real use cases, but they're not typical solo developer problems.

My honest advice for solo developers. Start with Railway (or Render, or Fly.io). Ship your product. Grow your user base. If you eventually hit the limits of managed platforms, that's a good problem to have, and you can migrate to AWS with actual revenue to justify the complexity. Don't start on AWS because it seems "more professional." Start where you can ship the fastest.