AWS, Cloudflare, Supabase and others: which one to choose?

Choosing the right cloud provider is one of the most consequential decisions for any software project, because it shapes costs, scalability, and long-term maintainability. The market is broader and more differentiated than ever: from generalist platforms like AWS and Google Cloud to more focused solutions like Supabase or Cloudflare, each with strengths and limitations worth examining carefully before committing.

AWS: the complete solution for every need

Amazon Web Services is the undisputed market leader, with a service catalogue covering compute (EC2), storage (S3), relational databases (RDS), and advanced machine learning tools like SageMaker. Its ISO 27001 certification makes it suitable for organizations with strict compliance requirements. The downside is a pay-as-you-go pricing model that can become difficult to predict for complex projects, paired with a steep learning curve and a real risk of vendor lock-in as architectures grow more deeply integrated.

Cloudflare: security and performance for the web

Cloudflare excels at protecting and optimizing web applications, offering a global CDN, managed DNS, advanced firewall, and serverless functions through Workers. Its Zero Trust model enables secure access to corporate resources and the platform is ISO 27001 certified. It remains a supporting layer rather than a complete application platform, though: it is not designed for complex backends, and the more advanced features like custom firewalls or granular traffic analytics require paid plans that can become significant for larger organizations.

Supabase: open source and simplicity for developers

Supabase is an open-source platform that simplifies backend development through a fully managed PostgreSQL database, built-in authentication with OAuth and SSO, serverless functions, and configurable storage for files and images. It is especially valued by small teams and startups for fast setup and a generous free tier. It lacks advanced security certifications like ISO 27001, making it less appropriate for regulated environments, and its reliance on PostgreSQL can be a constraint for architectures that require non-relational databases or hybrid data models.

Google Cloud Platform (GCP): scalable alternative to AWS

Google Cloud is the leading alternative to AWS for teams working with large data volumes and artificial intelligence, thanks to BigQuery for advanced analytics and Vertex AI for machine learning. It offers ISO 27001 certification and an initial credit to trial services. Its community is smaller than AWS’s, services like BigQuery can become expensive quickly with large datasets, and technological lock-in is a risk to weigh before building deeply integrated architectures.

Microsoft Azure: perfect for Microsoft companies

Azure is the natural choice for organizations already operating within the Microsoft ecosystem, with native integration across Office 365, Windows Server, and Active Directory, and solid support for hybrid architectures that combine on-premises infrastructure with cloud workloads. The flexible pay-as-you-go model includes tools to monitor and optimize spending. The interface can feel less intuitive than AWS or GCP, some services require additional licensing, and the platform loses appeal for teams working in multi-platform environments without existing dependencies on the Microsoft stack.

DigitalOcean: the choice for startups and developers

DigitalOcean stands out for its ease of use and competitive pricing, with virtual servers (Droplets), managed PostgreSQL and MySQL databases, and Kubernetes support for container orchestration. Entry-level plans start at a few dollars per month, making it an attractive option for startups and agile teams. The service catalogue is less comprehensive than larger providers, mature solutions for data analytics and AI are absent, and customer support is less structured; it is not always the best fit for projects with highly variable or very demanding workloads.

Vercel and Netlify: for modern front-end

Vercel and Netlify are the reference platforms for deploying web applications built on front-end frameworks like React and Next.js, with static and dynamic hosting, an integrated CDN, and automated build pipelines. Both offer generous free tiers for personal projects and include serverless functions for simple backend logic. They are not suited to complex backends, enterprise plans can become costly for large teams, and their value diminishes considerably outside the React ecosystem and compatible frameworks.

Heroku: PaaS for rapid development

Heroku is a PaaS that enables deployment of applications in Python, Node.js, Ruby, and other popular languages in just a few commands, backed by a wide add-on ecosystem for databases, queues, and analytics tools. It is appreciated for quick onboarding, but paid plans are often more expensive than DigitalOcean or AWS for equivalent resources, scalability has clear limits under heavy load, and the free tier offers only the most basic functionality.

Which one to choose?

There is no universal answer: the right choice depends on project type, budget, team size, and compliance requirements. Teams seeking speed and simplicity will find a solid starting point in Supabase or DigitalOcean, while complex projects with high security needs will gravitate toward AWS, Google Cloud, or Azure. Cloudflare is the natural fit for protecting and optimizing existing sites, Vercel and Netlify for front-end development, and Heroku for teams that need to reach production very quickly. Analyzing long-term requirements and learning from teams that have faced similar decisions remains the most effective way to choose with confidence.