AWS vs Google Cloud for Backends in 2026

For a backend team, the AWS versus Google Cloud question is less about which provider is better overall and more about what an API with a Postgres database, a queue, file storage and a few scheduled jobs looks like on each, and both run that stack well while differing in how many services you assemble it from, how identity and networking work, how billing behaves at low and steady traffic, and which one your customers, investors or hires expect.

This guide compares them service by service for that backend, then covers pricing, credits and how to keep the decision reversible.

AWS vs Google Cloud at a glance

Compute: Fargate and Lambda vs Cloud Run

On AWS, a containerized API typically runs as an ECS service on Fargate behind an Application Load Balancer, which means a cluster, a task definition, a service, a target group and security groups. Lambda covers function workloads with its own limits.

Cloud Run takes a container image and returns an HTTPS URL, with autoscaling and scale to zero built in. For a single service it is the shortest path from image to production on either cloud. Larger setups on GCP move to GKE, where Autopilot manages the nodes. On AWS, EKS is the Kubernetes option, with more add-ons to install and manage yourself.

Databases: RDS vs Cloud SQL

Both offer managed PostgreSQL with automated backups, point-in-time recovery, read replicas and a standby in a second zone. RDS supports more engines and has Aurora as a higher tier with storage that grows on its own. Cloud SQL has Enterprise and Enterprise Plus editions, and AlloyDB as its higher-performance Postgres-compatible tier. Connecting differs: RDS lives in your VPC and is reached by security group rules, while Cloud SQL is usually reached through private IP or the Cloud SQL Auth Proxy with IAM. RDS vs Cloud SQL goes deeper.

Messaging: SQS and SNS vs Pub/Sub

AWS splits messaging into SQS queues, SNS topics for fan-out and EventBridge for event routing, and a typical publish-subscribe setup combines an SNS topic with one SQS queue and dead-letter queue per consumer. Google Cloud Pub/Sub covers both patterns with topics and subscriptions, plus dead-letter topics, ordering keys and push or pull delivery, so there is less to wire up. Pub/Sub vs SQS compares them in detail.

Storage: S3 vs Cloud Storage

S3 and Cloud Storage are close in features: strong consistency, versioning, lifecycle rules, signed URLs and several storage classes. Cloud Storage also offers dual-region and multi-region buckets as a location setting, while S3 buckets are regional with replication as a separate configuration. See S3 vs Google Cloud Storage.

IAM and networking

Identity and networking are where daily work differs most, starting with how permissions attach. AWS IAM attaches policies to roles, users and resources, with resource policies on S3 buckets and SQS queues adding a second layer, and account boundaries separating environments. Google Cloud grants roles to principals at the organization, folder, project or resource level, and workloads run as service accounts, so a project per environment is the usual isolation.

AWS VPCs are regional, and private subnets need NAT gateways for outbound traffic, which bill per hour and per GB. Google Cloud VPCs are global, with subnets per region, and Cloud NAT is configured per region. Both charge for internet egress and cross-region traffic.

Pricing and credits

List prices for comparable compute, storage and database instances are close, and architecture choices such as NAT gateways, idle capacity and egress usually move the bill more than the provider does. Google Cloud applies sustained use discounts automatically on some Compute Engine machine types and offers committed use discounts. AWS discounts come from Savings Plans and Reserved Instances bought for one or three years. Both run startup programs with credits, which for an early company can outweigh every other cost difference for a year or more.

Deploy the same backend to either with Encore

Encore combines an open source infrastructure SDK with a platform that provisions and deploys into your own AWS or GCP account. It is infrastructure from code: the application declares what it uses, and the provider is chosen per environment, so the AWS versus GCP decision stops being written into the code. A Go service declares a database, a topic, a bucket and a cache keyspace the same way for both:

package orders

import (
	"encore.dev/pubsub"
	"encore.dev/storage/cache"
	"encore.dev/storage/objects"
	"encore.dev/storage/sqldb"
)

var db = sqldb.NewDatabase("orders", sqldb.DatabaseConfig{Migrations: "./migrations"})

type OrderPlaced struct{ ID int64 }

var Placed = pubsub.NewTopic[*OrderPlaced]("order-placed", pubsub.TopicConfig{
	DeliveryGuarantee: pubsub.AtLeastOnce,
})

var invoices = objects.NewBucket("invoices", objects.BucketConfig{})

var cluster = cache.NewCluster("orders-cache", cache.ClusterConfig{
	EvictionPolicy: cache.AllKeysLRU,
})

What each declaration becomes depends on the environment's cloud, per the AWS and GCP infrastructure docs:

Encore provisions an IAM role for the service on AWS and a service account per service on GCP. encore run starts Postgres locally along with the topic, bucket and cache, so development does not depend on either cloud. A team can start on GCP credits and add an AWS environment when an enterprise customer requires it, from the same code, after connecting the second account.

Best fit: teams that want to pick AWS or GCP per environment, or keep the option to move, without maintaining two sets of infrastructure code.

How to choose

Pick AWS when customers, compliance requirements or your team's experience point to it, or when you need a service only AWS offers. Pick Google Cloud when you want the shortest path to a container backend with Cloud Run, a simpler messaging and project model, or when its credits are the better offer. If the decision is not clear yet, keep it reversible by keeping provider-specific infrastructure code out of the application.

Related guides

• How to deploy to GCP in 2026
• Cloud Run vs Fargate
• DigitalOcean vs AWS
• Google Cloud pricing
• Comparison: AWS, Azure, and GCP