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    AWSvsAzurevsGCP:HowtoChooseforYourProduct

    The best cloud provider is the one your team can use most effectively. Here is how to evaluate AWS, Azure, and GCP for your specific product and context — without the marketing noise.

    September 29, 20257 min read
    AWSAzureGCPcloudinfrastructure
    AWS vs Azure vs GCP: How to Choose for Your Product

    AWS, Azure, and Google Cloud Platform can each run any modern application competently. The choice between them is rarely determined by capability — it is determined by ecosystem fit, team familiarity, existing enterprise agreements, and the specific services your architecture requires.

    AWS: The Default for Startups

    AWS has the largest service catalogue, the deepest ecosystem of third-party integrations, and the largest community of engineers with hands-on experience. For startups without an existing cloud commitment, AWS is the lowest-risk choice. The startup credit programs and the breadth of managed services for every common use case make it the default for new projects.

    • Best for: General-purpose applications, serverless, containerised workloads.
    • Strongest services: Lambda, RDS, S3, CloudFront, ECS/EKS, SQS, Bedrock.
    • Considerations: Complex IAM model, service count can be overwhelming, pricing complexity.

    Azure: Enterprise and Microsoft Stack

    Azure is the natural choice for organisations deeply embedded in the Microsoft ecosystem — Active Directory, Office 365, SQL Server, .NET. The enterprise integration story is excellent. Azure also has the strongest compliance portfolio for regulated industries, particularly in Europe.

    • Best for: Microsoft-stack enterprises, heavily regulated industries, European data residency.
    • Strongest services: Azure AD, SQL Managed Instance, Azure DevOps, Power Platform.
    • Considerations: Developer experience historically weaker than AWS, though improved significantly.

    GCP: Data, ML, and Kubernetes

    GCP leads on managed Kubernetes (GKE), BigQuery for analytics, and AI/ML services (Vertex AI). If your architecture is data-intensive or heavily AI-driven, GCP's managed services may offer meaningful advantages. Google's internal infrastructure expertise shows in the quality of its data and container services.

    • Best for: Data-intensive products, ML/AI workloads, Kubernetes-first architectures.
    • Strongest services: BigQuery, GKE, Vertex AI, Cloud Spanner, Pub/Sub.
    • Considerations: Smaller ecosystem and community than AWS, fewer third-party integrations.

    Need help choosing and configuring your cloud infrastructure?

    Asquarify has deployed products on all three major clouds. We will help you choose and set it up correctly from the start.

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