Amazon Web Services vs Google Cloud Platform
Two hyperscaler cloud options for hosting. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.
Which fits you
- The widest catalog of building blocks — Lambda, containers, managed databases, queues — to assemble your own infrastructure.
Use it whenYou need a specific AWS service, enterprise customers ask for it, or you have credits to spend.
Trade-offYou wire up networking, permissions and deploys yourself; billing is per service and hard to predict.
- Containers on Cloud Run that scale to zero, next to BigQuery, Firebase and Google's AI services.
Use it whenYour product leans on BigQuery, Vertex AI or Firebase, or you have Google Cloud credits.
Trade-offMore setup than a PaaS, and IAM and billing take learning.
At a glance
| Used by | 386 makers' products · 17 open-source projects | 184 makers' products |
|---|---|---|
| Cost at default usagerequests 5 million requests, data transfer out 100 GB, serverless function compute 100 GB-hours | $17/mo Pay as you go (Lambda + EC2 t4g.small) | — |
| Downloads | 4.2M/wk−39% vs npm | |
| Pricing | Pay-as-you-go per service; new accounts get up to $200 in Free Tier credits over 6 months. · paid from Pay as you go | Pay-as-you-go per service; new customers get $300 in free credit, plus free monthly usage of 20+ products. · paid from Pay as you go |
| Free tier | Yes | Yes |
| Open source | No | No |
What makers say
Makers on using it for hosting, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.
We are so excited to integrate with AWS Lambda. Look for our upcoming co-authored blog about how Fleak and AWS Lambda bring goodness to data teams and help them win their time back!
AWS provides the global infrastructure we need to deliver low-latency voice translation to users worldwide. Their reliable services ensure our calls connect seamlessly across regions.
AWS Lambda's scalability is definitely a game-changer, especially for handling the traffic spikes from a Product Hunt launch. Shoutout to AWS Lambda for making it possible! 🚀
GCP has been solid for our AI infra stack, especially around inference and data pipelines. The tooling is consistent, and the managed services scale with less hand-holding than most
GCP gives us scalable infra with minimal friction. Their tooling around AI workloads has improved significantly in the past year. Easy integration with AI pipelines and generous scaling.
i self host everything on GCP and am super thankful to their startup team and program for giving me some credits to get integral off the ground. great product and support.
Loved and watch-outs
Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.

