Honest, experience-based cloud platforms comparison from engineers who have shipped production systems with both.
AWS vs Google Cloud: AWS is the market leader with the broadest service portfolio. Google Cloud excels in AI/ML, data analytics, and Kubernetes. Choose based on your specific workload requirements. Need help choosing? Get a free consultation →
3
AWS Wins
0
Ties
3
Google Cloud Wins
AWS vs Google Cloud: AWS wins for breadth — 200+ services, biggest market share, widest certifications pool. GCP wins for BigQuery, Vertex AI, and Kubernetes-native workflows. AWS broader; GCP sharper.
AWS holds ~31% cloud infrastructure market share vs Google Cloud's ~11% (Synergy Research, Q4 2024). AWS: 34 regions, 108 AZs, 200+ services. Google Cloud: 40 regions, 121 zones, ~150+ services. Compute pricing (on-demand general-purpose, us-east, 4 vCPU/16 GB): AWS m7i.xlarge ~$0.1792/hr; GCP e2-standard-4 ~$0.1340/hr with automatic sustained-use discount. Google Cloud leads in AI/ML (Vertex AI, TPUs, Gemini), data warehousing (BigQuery), and managed Kubernetes (GKE — Google invented K8s). AWS leads in service breadth, serverless ecosystem (Lambda), and enterprise adoption. Pick AWS for widest catalog and largest hiring pool; Google Cloud for AI-heavy workloads, BigQuery analytics, and Kubernetes-first architectures.
| Criteria | AWS | Google Cloud | Winner |
|---|---|---|---|
| Service Breadth | 10/10 | 8/10 | AWS |
WhyAWS offers 200+ services — the widest catalog of any cloud provider. Google Cloud has fewer services but covers all major categories well. | |||
| AI/ML Services | 8/10 | 10/10 | Google Cloud |
WhyGoogle Cloud leads in AI/ML: Vertex AI, TPUs, BigQuery ML, and pre-trained models. Google's research heritage (TensorFlow, BERT, Transformer) gives it a genuine edge. | |||
| Kubernetes | 8/10 | 10/10 | Google Cloud |
WhyGoogle invented Kubernetes. GKE is widely considered the best managed Kubernetes service — more stable, faster updates, and better auto-scaling than EKS. | |||
| Enterprise Adoption | 10/10 | 7/10 | AWS |
WhyAWS holds ~32% market share and is the default choice for most enterprises. More companies have AWS expertise, making it easier to hire and find support. | |||
| Pricing | 7/10 | 9/10 | Google Cloud |
WhyGoogle Cloud offers sustained-use discounts automatically, per-second billing, and generally more transparent pricing. AWS pricing is complex but offers Reserved Instances for cost savings. | |||
| Serverless | 10/10 | 8/10 | AWS |
WhyAWS Lambda is the most mature serverless platform with the largest ecosystem of triggers and integrations. Cloud Functions is solid but less feature-rich. | |||
Scores use a 1–10 scale anchored to production behavior, not vendor marketing. 10 = production-proven at scale across multiple ZTABS deliveries with no recurring failure modes; 8–9 = reliable with documented edge cases; 6–7 = workable but with caveats that affect specific workloads; 4–5 = prototype-grade or stable only in a narrow slice; below 4 = avoid for new work. Inputs: vendor docs, GitHub issue patterns over the last 12 months, our own deployments, and benchmark data cited in the table when applicable.
Vendor-documented numbers and published benchmarks. Sources cited inline.
| Metric | AWS | Google Cloud | Source |
|---|---|---|---|
| Global cloud market share (recent) | Clear #1 share | Top-3 share | srgresearch.com/articles — Synergy Research quarterly reports |
| Regions / AZs | 34 regions, 108 AZs | 40 regions, 121 zones | aws.amazon.com/about-aws/global-infrastructure · cloud.google.com/about/locations |
| Compute: 4 vCPU / 16 GB on-demand (us-east) | m7i.xlarge ~$0.1792/hr | e2-standard-4 ~$0.1340/hr (sustained-use auto-discount) | aws.amazon.com/ec2/pricing · cloud.google.com/compute/vm-instance-pricing |
| Object storage (standard tier, GB/mo, us-east) | S3 Standard ~$0.023 | Cloud Storage Standard ~$0.020 | aws.amazon.com/s3/pricing · cloud.google.com/storage/pricing |
| Egress to public internet (first 10 TB/mo) | $0.09/GB (US regions) | $0.12/GB (standard tier, Americas) | Vendor pricing pages |
| Managed Kubernetes — control plane | EKS $0.10/cluster/hr (~$73/mo) | GKE Autopilot/Standard: $0.10/cluster/hr (1st cluster free per zone/region per billing account) | aws.amazon.com/eks/pricing · cloud.google.com/kubernetes-engine/pricing |
| Serverless compute — request pricing | Lambda: $0.20 per 1M requests + duration | Cloud Functions 2nd gen: $0.40/M (above 2M free) + duration | Vendor pricing |
| Data warehouse — 1 TB query cost | Redshift ra3.xlplus: ~$1/hr cluster-based | BigQuery on-demand: $6.25/TB scanned (1 TB free/mo) | Vendor pricing |
| Premier AI/ML service | SageMaker + Bedrock (Claude, Llama, Titan) | Vertex AI + Gemini 1.5/2.0 models + TPU v5 | aws.amazon.com/bedrock · cloud.google.com/vertex-ai |
| Free tier (12-mo intro compute) | t2/t3.micro 750 hrs/mo for 12 months | e2-micro 730 hrs/mo always-free (US-only), $300 credits × 90 days | Vendor free-tier pages |
| Certification ecosystem — practitioners (US) | Very large AWS-certified pool | Smaller but growing Google Cloud pool | LinkedIn people search; indicative |
AWS has the most migration tools, largest partner network, and most enterprise expertise.
Google Cloud's Vertex AI, TPUs, and BigQuery ML provide the best integrated AI infrastructure.
GKE is the gold standard for managed Kubernetes — created by the team that invented Kubernetes.
AWS Lambda has the most triggers, longest track record, and largest serverless ecosystem.
The best technology choice depends on your specific context: team skills, project timeline, scaling requirements, and budget. We have built production systems with both AWS and Google Cloud — talk to us before committing to a stack.
We do not believe in one-size-fits-all technology recommendations. Every project we take on starts with understanding the client's constraints and goals, then recommending the technology that minimizes risk and maximizes delivery speed.
Based on 500+ migration projects ZTABS has delivered. Ranges include engineering time, QA, and a typical 15% contingency.
| Project Size | Typical Cost & Timeline |
|---|---|
| Small (MVP / single service) | $5K–$25K, 2–6 weeks. <10 services (EC2, S3, RDS, ELB). Lift-and-shift via Migrate for Compute Engine (M4CE) handles VMs; IAM + networking re-architecture is the majority of the work. |
| Medium (multi-feature product) | $30K–$150K, 10–24 weeks. 20-80 services. Lambda → Cloud Functions rewrite (different runtime versions, different trigger model). RDS → Cloud SQL or AlloyDB migration via DMS. Plan 4-6 weeks of parallel running with DNS-level traffic shifting. |
| Large (enterprise / multi-tenant) | $200K–$1.5M+, 8–18 months. Enterprise-scale: IAM policy translation, VPC peering re-architecture, Data Warehouse migration (Redshift → BigQuery often a net win for analytics teams, but ~3 months of query rewrite). Audit all SaaS licenses for GCP-equivalent contracts. |
Under ~$5K/month spend, cost differences are small — pick by team skill. Past ~$50K/month, GCP's sustained-use discounts (automatic) and BigQuery pricing can undercut AWS 10-30% on data workloads; AWS wins on edge and breadth of savings plans.
Specific production failures we have seen during cross-stack migrations.
AWS IAM is resource + principal + action; GCP uses projects + roles with org hierarchy. Porting permission models 1:1 usually breaks — redesign from GCP projects / AWS accounts upward.
Moving TBs of data between clouds costs $0.08-0.12/GB. A 10 TB migration runs $800-1,200 just on egress. Use Snowball/Transfer Appliance or plan for a phased cutover.
Third-way tools and approaches teams evaluate when neither side of the main comparison fits.
| Alternative | Best For | Pricing | Biggest Gotcha |
|---|---|---|---|
| Azure | Microsoft-shop enterprises using Active Directory, Office 365, and.NET. | Comparable to AWS; generous enterprise discount programs. | Portal UX is inconsistent; some services lag AWS/GCP feature parity. |
| DigitalOcean | Startups and indie devs wanting simple, predictable pricing and fast spin-up. | Droplets from $4/mo; App Platform from $5/mo. | Fewer managed services — no equivalent to Lambda, DynamoDB, BigQuery. |
| Cloudflare (Workers/R2/D1) | Edge-first apps where global low-latency and egress-free storage matter. | Workers from $5/mo (10M req); R2 $0.015/GB no egress. | Workers has tight CPU/memory limits; D1 and Durable Objects still maturing. |
| Hetzner (self-host) | Teams comfortable with ops wanting 60-80% lower bills for the same compute. | Dedicated servers from ~$40/mo; no egress fees up to stated limits. | You own uptime, backups, patching, and security — no managed anything. |
Sometimes the honest answer is that this is the wrong comparison.
Both have steep learning curves and surprise bills. Fly.io, Railway, or Render are kinder for low-traffic personal projects.
If your identity, Office, and dev tools are all Microsoft, Azure pays dividends AWS and GCP cannot match. Revisit AWS/GCP when you are multi-cloud ready.
Verified reviews from clients who shipped production systems on stacks we recommended.
Verified reviews from real client engagements — sourced from our public testimonial archive and Clutch profile.
My experience is throughout positive. Communication, service, the short response times and the flawless execution of a challenging topic was absolutely great. ZTABS is definitely my first choice again.
Christian Neff
Bank Software Advisory · Bank Software Advisory
Fintech
Fantastic Agency! I couldn't fault them even if I tried. They always go above and beyond to meet your expectations and always produces quality work. Thank you ZTABS.
Stephanie Kal
CEO · Beauty Finder Australia
Marketplace
It has been great working with ZTABS. They bounce off the ideas along the way. Amazing Experience.
Joel Rowe
CEO · Drill Quoter
Marketplace
We do not just consult on stack choices — we build, run, and maintain production products on these stacks.
We don't just contract — we ship and operate our own software. 17 products in production.
Our senior architects have shipped 500+ projects with both technologies. Get a free consultation — we will recommend the best fit for your specific project.
