Railway vs AWS: Which Should You Pick for Your AI Backend?

We get this consulting question constantly: "We're building an AI app — should we use Railway or AWS?" Here's the honest answer, with our actual numbers from running the Aether AI backend.

TL;DR

• Use Railway if you're solo, a small team, your monthly compute bill is below ~$300, or you value shipping speed over scale headroom.
• Use AWS if you need fine-grained networking, compliance certifications (HIPAA, SOC 2), VPC peering, or you're spending >$1K/month and the per-unit cost matters.
• Use both in stages — start on Railway, migrate to AWS when traffic and team size justify the operational overhead.

Developer experience: not even close

Railway is what AWS Lambda or Elastic Beanstalk should have been. You connect your GitHub repo, push code, and Railway builds + deploys + gives you a URL. Environment variables in a clean UI. Database provisioning in two clicks. Built-in metrics. Auto-deploy on git push.

AWS, even with all the modern conveniences (Amplify, App Runner, CDK), still expects you to think in primitives: VPC, subnet, IAM role, security group, target group, ALB, ECS task definition, CloudWatch log group. None of this is hard, but all of it is overhead that doesn't add value to your product.

For a solo developer or 2-person team, Railway will save you a full work-week per year in YAML wrangling alone.

Real pricing comparison

Apples-to-apples for a small Node.js API serving Claude proxy traffic:

Railway

• Hobby plan: $5/mo + $0.000463/GB-hour memory, $0.000231/vCPU-hour
• Pro plan: $20/mo + same usage rates
• Idle services pause and don't bill — huge for staging environments

AWS

• t4g.micro EC2: ~$6/mo (always-on)
• + ELB: ~$16/mo
• + Cloudwatch logs: variable, ~$3–10/mo realistic
• + data transfer: $0.09/GB egress after 100GB free tier
• + Route 53: $0.50/mo + queries

For small workloads, Railway is dramatically simpler and often cheaper. For workloads that benefit from AWS spot instances, reserved instances, or Savings Plans, AWS gets cheaper at scale.

When you outgrow Railway

The honest limits:

• Network features. Railway has no VPC peering, no private link, no Transit Gateway. If you need to connect to enterprise customers' networks, you need AWS.
• Compliance. Railway has SOC 2 but not HIPAA BAA, FedRAMP, etc. Regulated industries need AWS or GCP.
• Specific services. Need EventBridge, SQS FIFO with content-based dedup, Step Functions, Athena? You need AWS.
• Cost at scale. Above ~$2K/month, Railway's simplicity premium starts costing you. AWS reservation discounts can cut bills 30–60%.
• Spot instances. If your workload is fault-tolerant batch (training, ETL), AWS Spot is 60–90% cheaper than any always-on option.

Our actual Aether AI numbers

Running the Claude proxy backend for both RDR2 Companion and (soon) GTA V Companion:

• Railway bill (May 2026): $7.42
• Anthropic API bill (May 2026): ~$45 (varies with traffic)
• Total infrastructure: ~$53/month for a live App Store backend

Could we run this on AWS for less? Probably. AWS t4g.micro + minimal everything could be $15/month. But the migration would take a weekend and produce zero new features. At our current scale, Railway's developer-experience premium is worth it.

When we hit ~5K monthly active users across the Aether AI platform, we'll re-evaluate. By then we'll have actual traffic patterns to optimize against.

The hybrid approach

What sophisticated teams actually do:

• Railway for everything user-facing — your API, web frontend, staging environments. Fast iteration matters most here.
• AWS for everything specialized — Bedrock if you need it, S3 for large object storage (cheaper than Railway storage), CloudFront for CDN, Athena for analytics queries.
• Cloudflare for the edge layer — DNS, DDoS protection, R2 storage with zero egress fees, Workers for low-latency edge logic.

You can mix these cleanly because they all do well-defined jobs. No vendor lock-in if you keep your application code portable.

Our recommendation

If you're starting today:

1. Start on Railway. Ship something this week.
2. Don't optimize for scale you don't have yet. Premature AWS migration is a leading cause of stalled startups.
3. Architect portably. Use environment variables, avoid Railway-specific APIs, use standard Postgres/Redis. Migration day, when it comes, will be a weekend, not a quarter.
4. Re-evaluate at $500/mo Railway spend or when a customer requires specific compliance.

If you'd like help architecting an AI backend that won't paint you into a corner, book a call. We've done this dance.