What are the big 3 clouds?

What Are the Big 3 Clouds: AWS, Azure, and GCP Market Share

Understanding the what are the big 3 clouds landscape helps navigate modern digital infrastructure. These platforms provide essential services powering the internet, yet their specific market positions differ significantly. Learning these foundational differences allows businesses to select the provider best suited for their unique data and enterprise operational requirements.

What are the big 3 clouds in computing?

The term Big 3 refers to the dominant trio of cloud computing platforms that power most of the modern internet: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Collectively, these industry giants account for 63-66% of total global cloud infrastructure spending. ^[1]

Most enterprises rely on at least one of these providers to host applications, manage data, and run machine learning models. Understanding why they hold this market position requires a look at their individual strengths.

Amazon Web Services (AWS)

AWS currently holds approximately 30% of the market,^[2] maintaining its position as the pioneer and largest provider in the cloud infrastructure space. It offers the most massive, mature ecosystem of services available today.

I remember my first encounter with AWS - the sheer number of services felt overwhelming. It takes time to master, but the depth of their toolset is unmatched, particularly for complex serverless architectures.

Microsoft Azure

Microsoft Azure trails as the second-largest provider, capturing about 20% of the market share. ^[3] Its primary appeal lies in its seamless integration with enterprise environments.

If a company already uses Windows Server, Active Directory, or Office 365, Azure feels like a natural extension of their existing infrastructure. This ease of migration keeps many large organizations committed to the Microsoft ecosystem.

Google Cloud Platform (GCP)

Google Cloud Platform holds around 13% of the market,^[4] though it is recognized as the fastest-growing contender. It distinguishes itself through expertise in data-heavy workloads.

GCP is the gold standard for companies leveraging top 3 cloud providers to facilitate cutting-edge data analytics, artificial intelligence, and machine learning. Its native support for Kubernetes - an open-source system Google originally developed - makes it a favorite for modern containerized deployments.

The Cloud Distinction: Computing vs. Meteorology

It is worth noting that the term cloud also refers to the three foundational types of atmospheric formations categorized by Luke Howard. While unrelated to IT infrastructure, this often causes confusion when analyzing the difference between AWS Azure and Google Cloud.

The three primary types include Cirrus, which are high-altitude and wispy; Cumulus, defined by their fluffy, cotton-like appearance; and Stratus, which appear as low, uniform blankets of fog-like coverage. Understanding these distinctions helps clarify the different ways the term is used.

Comparing the Big 3 Cloud Providers

AWS

- Large-scale, diverse, and complex enterprise deployments

- Longest track record with the broadest service catalog

Microsoft Azure

- Organizations heavily invested in Windows and Microsoft 365

- Seamless integration with Microsoft software stacks

GCP

- High-performance data science and containerized apps

- Superior data analytics and ML training capabilities

Choosing the Right Cloud for a Growing Startup

Minh, a software architect in Ho Chi Minh City, spent weeks deciding which cloud to use for his new fintech app. He initially thought AWS was the only choice due to its popularity.

The team tried migrating their existing services to AWS but struggled with complex permission management and high monthly costs that the startup could barely afford.

After a difficult month of troubleshooting, they realized their workload was primarily data analysis and containerized microservices. They switched the analytics portion to Google Cloud.

The result was a 40% reduction in processing time for their core data reports within 30 days. Minh learned that choosing a cloud provider based on specific workload needs is better than just following the herd.