# AWS vs Google Cloud

URL: https://softwaredictionary.org/compare/aws-vs-google-cloud
Last updated: 2026-10-06

In short: Both are full public clouds. AWS has the broadest catalog and ecosystem; Google Cloud is known for data analytics, AI, Kubernetes and its global network.

## What is the difference between AWS and Google Cloud?

Amazon Web Services launched its core services in 2006 and became the first large public cloud. Google Cloud grew from App Engine, launched in 2008, into a full platform running on the same infrastructure as Google's own products. Both offer virtual machines, containers and Kubernetes, serverless functions, object storage, managed databases, networking, analytics and AI in regions around the world.

Their core services map closely. EC2 corresponds to Compute Engine, S3 to Cloud Storage, Lambda to Cloud Run functions, EKS to GKE, RDS to Cloud SQL, DynamoDB to Firestore or Bigtable, and Redshift to BigQuery. They organize resources differently: AWS groups them in accounts, often many per company under AWS Organizations, while Google Cloud groups them in projects, each with its own permissions, enabled APIs and billing.

Each has its strengths. AWS offers the widest range of services and the largest community, partner network and pool of experienced engineers, so third-party tools and tutorials often target it first. Google Cloud stands out in data and AI with BigQuery and Vertex AI, in containers with GKE, since Kubernetes started at Google, and in running traffic over its private global network.

A common misconception is that one is simply cheaper or better. Prices depend on the exact services, region, usage pattern and discounts, and both run reliably at huge scale. The choice usually follows the team's skills, the services a project depends on, such as BigQuery or a particular AWS service, and where partners and existing systems already run.

| Aspect | AWS | Google Cloud |
| --- | --- | --- |
| Launched | 2006, with S3 and EC2 | 2008, with App Engine |
| Virtual machines | EC2 | Compute Engine |
| Object storage | S3 | Cloud Storage |
| Serverless | Lambda | Cloud Run and Cloud Run functions |
| Managed Kubernetes | EKS | GKE |
| Data warehouse | Redshift | BigQuery |
| Resource organization | Accounts, grouped with AWS Organizations | Projects, grouped in folders under an organization |
| Known for | The broadest catalog and the largest ecosystem | Data analytics, AI, Kubernetes and its global network |

## Choose AWS when

- You want the widest choice of services and third-party integrations.
- Your team, partners or hiring market already know AWS.
- You rely on a specific service that is most mature on AWS.

## Choose Google Cloud when

- Analytics on large datasets with BigQuery is central to your work.
- You run containers on Kubernetes or Cloud Run and want them well managed.
- You build with Google's AI models and tools through Vertex AI.
- You already use Firebase, which runs on Google Cloud projects.

## Frequently asked questions

**Is Google Cloud the same as GCP?**

Yes. Google Cloud Platform, or GCP, is the older name that many people still use for Google Cloud's infrastructure and services.

**Which is cheaper, AWS or Google Cloud?**

Neither is cheaper in general. Costs depend on the services, region, usage and discounts, and both offer free tiers and lower prices for committed use, so compare estimates for your own workload.

**Can I use AWS and Google Cloud together?**

Yes. Some companies run their main systems on AWS and their analytics in BigQuery, for example. Tools such as Terraform and Kubernetes keep deployments consistent, though moving data between clouds adds cost and complexity.

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