SaaS · Cloud

AWS vs GCP vs Azure: 2026 Startup Cost Comparison

Real-world cost breakdown for startups choosing AWS, GCP, or Azure — monthly bill differences and three structural factors that matter more than pricing.

Who should read this

TL;DR: For the same MVP workload, GCP runs roughly $30—50/month cheaper than AWS, and Azure is the most expensive unless you are on a Windows stack. Most of the cost gap comes not from the price sheet but from NAT Gateway charges, egress fees, and managed-service defaults. And as you move from Bootstrap to MVP to Growth, the “cheapest cloud” changes.

This article is for CTOs and backend leads at seed-to-Series A startups spending $200—$3,000/month on infrastructure. All prices are on-demand rates from each cloud’s official pricing pages as of April 2026, with no credits or Savings Plans applied.

At a glance: monthly cost across 3 stages and 3 clouds

StageWorkload profileAWSGCPAzure
BootstrapSolo dev, ~1K req/mo, 1 database$0—15$10—20$5—20
MVP3—5 people, ~50K req/mo, API + web split$120—160$70—110$90—130
Growth10+ people, ~500K req/mo, multi-service$350—500$220—360$310—520

AWS looks cheapest at the Bootstrap stage, but only because of the t4g.small free promotion (through December 2026) and the RDS Free Tier’s 750 hours. Once both expire, the AWS Bootstrap bill jumps to $40—60. There is no such thing as a “free cloud” — only a cloud where billing has not started yet.

Why the same workload costs different amounts

If you compare only the list price, per-vCPU hourly rates are nearly identical across all three clouds. The real differences come from three structural factors.

Free-tier design philosophy

AWS defaults to “free for 12 months.” The t4g.small 750 hours, RDS db.t4g.micro 750 hours, S3 5 GB — all expire 12 months after sign-up. When month 13 arrives, line items that were $0 suddenly start billing, adding $50—80 at once.

GCP runs Always Free tiers on Cloud Run, Cloud Functions, and parts of GCS with no 12-month limit. Cloud Run’s 180,000 vCPU-seconds per month (roughly 50 CPU-hours) is enough to run a Bootstrap-level SaaS API server at zero cost. The catch: Cloud SQL has no Always Free tier — even the smallest instance (db-f1-micro) costs $7+/month.

Azure uses a hybrid model — 12-month free offers plus some Always Free services. The App Service Free tier exists, but it lacks custom domains, SSL, and scale-out, making it unusable for production. In practice you start at B1 ($13.14/month).

Network and egress charges

All three clouds offer free inbound traffic but charge $0.08—0.12/GB for outbound (egress). So far, similar. The real divergence is in internal network charges.

AWS’s most notorious cost item is the NAT Gateway. Traffic from private subnets inside a VPC to the internet incurs $0.045/hour plus $0.045/GB for data processing. In a typical MVP stack, NAT Gateway alone can account for $32+ per month. GCP’s Cloud NAT has a similar structure but slightly lower data-processing fees. Azure’s NAT Gateway pricing is comparatively low, but outbound bandwidth kicks in at $0.087/GB after the first 5 GB.

Managed-service lock-in: fixed vs pay-per-use

Azure App Service uses per-instance fixed billing. The B1 tier costs $13.14/month whether you serve zero requests or 100K. Predictable, but wasteful at low utilization.

GCP Cloud Run bills on a request-based, pay-per-use model. You are charged only while a container is handling a request; when traffic drops to zero, the bill is $0. This is structurally favorable for early-stage startups with unpredictable traffic patterns.

AWS ECS Fargate bills by task runtime. The billing granularity is coarser than Cloud Run (1-minute minimum), and scale-to-zero is not the default — most teams keep at least one task running at all times. In practice, it behaves like a fixed cost.

AWS

Typical stack

EC2 t4g.small (or ECS Fargate) + RDS db.t4g.small (PostgreSQL) + S3 + CloudFront + Route 53.

Monthly cost breakdown

StageComputeDBStorage + CDNNATTotal
Bootstrapt4g.small free*RDS Free Tier*S3 ~$1$0—15
MVPFargate 2 tasks ~$36RDS db.t4g.small ~$25S3 + CF ~$10~$32$120—160
GrowthFargate 4 tasks ~$72RDS db.r6g.large ~$138S3 + CF ~$30~$45$350—500

* Expires December 2026. After that, Bootstrap costs rise to $40—60.

3 hidden costs

  1. NAT Gateway: Required by default in a VPC private-subnet setup. Often accounts for 20—25% of the total MVP bill.
  2. CloudWatch Logs: Default log retention is unlimited. Left unchecked, this quietly adds $10—30/month. Set retention to 7 or 30 days explicitly.
  3. Inter-AZ data transfer: Even within the same region, cross-AZ traffic costs $0.01/GB. Multi-AZ RDS makes this surprisingly expensive.

Operational complexity

AWS has the most granular IAM permission model of the three clouds, which also means the steepest initial setup curve. You have to design VPC networking (subnets, security groups, NAT) yourself, and while CloudWatch provides basic monitoring, custom dashboards cost extra. A 3—5 person team with no prior AWS experience can easily spend the first two weeks just on networking configuration.

GCP

Typical stack

Cloud Run + Cloud SQL (PostgreSQL) + GCS + Cloud Load Balancing.

Monthly cost breakdown

StageComputeDBStorage + LBCloud NATTotal
BootstrapCloud Run $0*Cloud SQL micro ~$7GCS ~$1$10—20
MVPCloud Run ~$15Cloud SQL small ~$30GCS + LB ~$20~$10$70—110
GrowthCloud Run ~$40Cloud SQL custom ~$90GCS + LB ~$35~$20$220—360

* Within the Always Free allowance (180,000 vCPU-seconds/month).

3 hidden costs

  1. Cloud SQL minimum cost: No Always Free tier, so even the smallest instance is $7/month — the “only fixed cost” at the Bootstrap stage.
  2. Cloud Logging volume: Log ingestion is on by default, and after 50 GB it costs $0.50/GB. Cloud Run’s stdout logs can generate surprisingly high volume.
  3. Premium Tier networking: GCP’s default network tier is Premium, making egress slightly more expensive than AWS. Switching to Standard Tier saves money but degrades performance.

Operational complexity

GCP’s strength is “opinionated defaults.” Cloud Run deploys with nothing more than a container image, and you barely need to know anything about networking. On the other hand, the project/folder/organization hierarchy is not intuitive, and service-account management gets confusing once it intersects with IAM roles. The Terraform provider also tends to lag behind AWS’s by one to two quarters.

Azure

Typical stack

App Service (B1—P1v3) + Azure SQL Database + Blob Storage + Azure Front Door.

Monthly cost breakdown

StageComputeDBStorage + CDNTotal
BootstrapApp Service Free to B1 ~$13Azure SQL Basic ~$5Blob ~$1$5—20
MVPApp Service B2 ~$26Azure SQL S2 ~$50Blob + FD ~$20$90—130
GrowthApp Service P1v3 ~$73Azure SQL GP 2—4 vCore $200—$400Blob + FD ~$40$310—520

3 hidden costs

  1. Outbound bandwidth: $0.087/GB after the first 5 GB. For JSON-heavy API responses, this adds $10—20/month at the MVP stage.
  2. Azure SQL DTU tier jump: When Standard S2 ($50/month) runs out of headroom, the next option is Premium P1 ($465/month) — nearly a 10x increase. Starting with the vCore model gives you an intermediate step (General Purpose 2 vCore at $201/month).
  3. Log Analytics volume: Once integrated with Application Insights, data ingestion is billed by volume. After the 5 GB/month free allowance, it costs $2.76/GB.

Operational complexity

Azure shines when you need tight integration with the Windows, .NET, and Active Directory ecosystem. If an enterprise customer requires AD-based SSO, Azure is the fastest path. For other stacks (Node, Python, Go), it actually gets in the way. The portal, CLI, and PowerShell coexist in a fragmented tooling landscape that makes automation scripts hard to keep consistent, and a poorly designed resource-group layout at the start is painful to restructure later.

Selection framework — tradeoffs by team context

AWSGCPAzure
Linux + open-source stack Good fitBest fitPoor fit
.NET / Windows stack WorkablePoor fitBest fit
Bursty traffic DecentBest fit (Cloud Run)Poor fit (fixed billing)
Steady, predictable traffic Best fit (RI/SP)DecentGood fit
Enterprise customers on board Good fitDecentBest fit (AD integration)
ML / TPU workloads DecentBest fitDecent
Terraform-centric IaC Best fitGood fitDecent
As of April 2026. 'Best fit' = strongest advantage for this condition, 'Good fit' = solid choice, 'Decent' = usable but no edge, 'Poor fit' = structurally disadvantaged.

Pitfalls to avoid — 5 failure modes

Decision flow

Does your stack depend on Windows, .NET, or Active Directory?
Yes → Go with Azure
No → Next question
Is ML / TPU or heavy GPU your core workload?
Yes → Go with GCP
No → Next question
Are you bootstrapped with highly variable traffic?
Yes → GCP Cloud Run (pay-per-use)
No → Next question
Strong Terraform experience and predictable traffic?
Yes → AWS + Savings Plans
No → Next question
Default: AWS -- the safest pick based on ecosystem breadth, documentation, and hiring pool
Narrow down your cloud choice in 5 questions. Walk top to bottom and stop at the first Yes.

Further reading