How do Vercel, AWS, Google Cloud, and Azure differ as deployment options?

How do Vercel, AWS, Google Cloud, and Azure differ as deployment options?

Vercel, AWS, Google Cloud, and Azure offer overlapping ways to deploy web applications, but the comparison depends on the specific service and configuration. A provider name alone does not tell you how much infrastructure work the team must perform.

For a wedding application, begin with requirements: the web framework, API runtime, database connectivity, background work, file storage, and the team's operating experience.

Compare concrete hosting services

Vercel provides documented integration for Next.js applications. Its Next.js guide explains supported deployment behavior, making framework fit a useful starting point.

AWS Amplify Hosting offers a Git-based deployment workflow for web applications, including supported server-rendered frameworks. AWS documents Amplify Hosting.

Google Cloud Run is a managed application platform for running code or containers. Google's Cloud Run overview describes its execution options.

Azure App Service hosts web applications and APIs using supported stacks or containers while managing underlying infrastructure. Microsoft's App Service overview explains that model.

Evaluate the complete operating picture

These examples show why the choice is not simply “managed hosting versus virtual machines.” Large cloud providers also offer managed services, and each selected service has its own runtime, networking, scaling, and deployment behavior.

Compare how the wedding application connects to its database, handles image uploads, runs scheduled tasks, stores secrets, and exposes logs. Include the effort of operating several connected services.

Assess current costs using the expected workload rather than assuming one provider is always cheaper.

Validate the decision with a small deployment

Deploy a representative slice: login, one authorized database read, and one required integration. Check the actual deployment and debugging experience.

Record the service-specific assumptions and tradeoffs. AI can organize this comparison, but measured behavior and the team's requirements should decide which option fits the initial release.