As a startup founder, choosing the right cloud platform is one of your most important technology decisions. Getting it right from the start can help accelerate your growth.

Two top choices are Google Cloud Platform (GCP) and Amazon Web Services (AWS). Both are powerhouses in the cloud market, offering an enormous range of scalable, pay-as-you-go services. key differences may make one a better fit than the other in specific situations.

In this article, we'll thoroughly compare GCP and AWS to help you determine the optimal platform for your unique startup needs. We'll explore pricing, features, and which one thrives in different industries.

A Brief History of GCP and AWS

Both companies have revolutionized cloud computing since entering the market over a decade ago. AWS launched in 2006, allowing organizations to rent Amazon's computing infrastructure. GCP followed in 2008 by providing Google's technology stack externally.

Today, AWS dominates with over 30% of the market share. However, GCP has also rapidly grown and established strongholds in specific areas like AI/ML. Both continually roll out new services to remain on the cutting edge of cloud technology.

Though AWS came first, GCP has narrowed the gap by focusing on developer and customer experience. Its technology and services are based on Google's latest innovations like TensorFlow for machine learning.

AWS VS Google Cloud Platform

• Pricing Models

  At first glance, AWS tends to carry a lower upfront price tag. It's generally more economical for basic computing needs like VMs and storage usage.

  However, GCP frequently discounts costs heavily for large, long-term clients. It also offers grants of up to $350,000 for AI/ML startups through its Cloud Credits and Google for Startups program.

  Additionally, compute-heavy services like databases and machine learning can tilt the scales toward GCP being more budget-friendly in some cases. Its pricing is also transparent around bandwidth costs unlike AWS, which adds surprise fees in some regions.

  Whether you select AWS or GCP usually depends on the services needed versus upfront budget constraints. GCP works best where funding is tight or key projects rely on fields Google owns, like TensorFlow. AWS fits other types of startups seeking a lower baseline bill.

• Features

  When reviewing platform features, the differences start to emerge between AWS and GCP.

  AWS offers a broad range of computing, storage, and analytics services, making it a versatile platform that can handle a wide variety of use cases.

  However, it lacks specialization in certain domains that GCP leads, like:

  • Machine Learning: Google's strength lies in products like TensorFlow, Cloud TPUs, and Vertex AI for developers to easily build and deploy ML models at scale.
  • Data Analytics: GCP's BigQuery is a top-rated, cost-effective data warehouse. It offers machine learning capabilities on massive datasets through tools like Data Studio.
  • APIs and Serverless: Google has a leg up with services like Cloud Functions for fully managed, event-driven functions, and Endpoints for building and managing APIs.

  Conversely, AWS excels in areas such as:

  • General Computing: From EC2 virtual machines to S3 storage, AWS handles basic infrastructure needs better than any other provider.
  • Containers and Serverless: AWS leads container orchestration through products like ECS and fully manages FaaS with Lambda.
  • Mobile: AWS Mobile Hub simplifies building, testing, and monitoring mobile apps at scale.

  In summary, GCP is ideal for AI/ML-focused startups, while AWS is better suited for startups establishing general infrastructure or offering mobile products

• Community and Market Share

  When beginning your cloud journey, having a large, active community around your chosen platform is invaluable.

  • There are over 2x more GitHub projects using AWS than GCP. This means more free code samples and tutorials.
  • Job postings for AWS roles significantly outnumber those requiring GCP experience, showing more career pathways.
  • AWS has exponentially more questions asked on Stack Overflow, a trove of helpful user forums and answers.

  However, GCP is growing its communities rapidly. The gap will likely close over time as organizations shift workloads between providers.

  For startups, ecosystem size mostly matters when requiring heavy integration help or collaborative projects. Greenfield founders have the flexibility to grow with an upcoming platform's curve.

• Key Industries

  Two final considerations are the industries each platform caters best to due to built-in strengths:

  • Web/App Development: AWS' comprehensive set of PaaS tools makes it the smoothest path for building and deploying websites or applications. Services like API Gateway, Lambda, and Amplify propel this sector.
  • Data Science/AI: Google's decades of expertise in AI, combined with products like TPUs, Vertex AI, and Keras elevate GCP above all others for machine learning workloads.
  • Healthcare: GCV's focus on HIPAA compliance, identity management, and collaboration tools positions it as the recommended choice in this regulated field.

Summary

In summary, AWS remains the market leader in overall size and adoption, making it a generally safe default choice given its versatility. However, GCP is growing quickly and has proven itself as preferential for certain specialized workloads.

The choice ultimately depends on unique business and technical factors:

• Pricing models - GCP excels for large, data-heavy or AI projects leveraging discounts.
• Areas of focus - Choose GCP for machine learning or big data expertise. AWS works well for general applications.
• Growth strategies - AWS has broad global reach but GCP is expanding rapidly in targeted domains.
• Community support - Both have strong communities, but GCP support is growing substantially.
• Existing tools - GCP aligns well with Google services, and AWS integrates broadly.

While the platforms continuously update, evaluating drivers within your industry and model will help match capabilities to strategic goals, accelerating technology success. A thorough analysis reveals a better long-term cloud partner.