Amazon S3 vs Cloud Run (2026): Pricing, Features & Verdict

A

Why choose Amazon S3

• Higher Integration score (10/10 vs 8/10)
• Higher Analytics score (8/10 vs 6/10)
• Better fit for enterprise (9/10 vs 7/10)

C

Why choose Cloud Run

• Has a free plan (Amazon S3 does not)
• Higher Cost score (7/10 vs 5/10)
• Higher Ease of Use score (7/10 vs 5/10)

A

Amazon S3

Pros

• Very high scale: about 500 trillion objects stored and around 200 million requests per second, according to Wikipedia.
• The S3 API is the industry standard, so a wide range of tools and competing storage providers support it.
• Strong data protection: versioning, MFA Delete, Object Lock in compliance mode, and cross-Region replication with a time-bound SLA.
• Many storage classes, from Express One Zone to Glacier Deep Archive at about $0.001 per GB-month, let teams match cost to how often data is accessed.
• Reviews are consistently positive: about 4.7 out of 5 from more than 1,100 Capterra reviews.

Cons

• Internet egress costs about $0.09 per GB after the first free 100 GB a month, and competitors widely criticise these fees.
• Request, retrieval and lifecycle-transition fees make monthly bills hard to predict.
• Reviewers on Capterra and TrustRadius call the console navigation and user interface complex.
• The SLA pays only service credits toward future bills, never refunds, and infrequent-access classes have a lower 99% uptime threshold.

C

Cloud Run

Pros

• Scale-to-zero with request-based billing means idle services cost nothing beyond any minimum instances you set.
• It runs any container image, so there is no language or framework lock-in, and source deploys build images automatically.
• Services, jobs, worker pools, and functions on one platform cover HTTP APIs, batch work, and queue consumers alike.
• Every service gets managed HTTPS on run.app plus custom domains, with WebSockets, HTTP/2, and gRPC support.
• On-demand NVIDIA L4 GPUs billed per second make it practical to serve AI inference without managing GPU VMs.
• A 99.95% monthly uptime SLA applies for non-GPU services in most regions.

Cons

• Cold starts when scaling from zero are the most common complaint, and keeping minimum instances warm adds ongoing cost.
• Internet egress beyond 1 GiB, plus Cloud Build and Artifact Registry, are billed separately and can inflate bills.
• Setup requires a Google Cloud project, a billing account, and familiarity with IAM.
• GPU services must use instance-based billing, get no free tier, and are excluded from committed use discounts.
• Usage-based billing can spike from traffic surges or runaway loops unless you set budgets and alerts.