Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale.
The global cloud computing market is being driven by the increasing adoption of cloud-based services by businesses of all sizes. Cloud computing offers several benefits over traditional on-premises IT infrastructure, including scalability, flexibility, and cost-effectiveness.
The growth of the cloud computing market is also being driven by the increasing adoption of mobile devices and the growth of the Internet of Things (IoT). Mobile devices and IoT devices generate a large amount of data that can be stored and processed in the cloud.
Cloud computing is essential in today’s world. Almost 83% of the enterprises workload are running on the cloud. The global cloud computing market size was valued at $371.43 billion in 2021 and is projected to reach $832.10 billion by 2028, registering a CAGR of 15.7% from 2022 to 2028.
When it comes to cloud computing, three major players dominate the market: AWS (Amazon Web Services), Azure (Microsoft Azure), and GCP (Google Cloud Platform). Each of these cloud providers offers a wide range of services and features, making it essential to understand their differences to make an informed decision for your organization’s cloud infrastructure. Let’s compare AWS, Azure, and GCP across various aspects:
What are the key differences between AWS, Azure, and GCP?
AWS, Azure, and GCP are all great cloud computing platforms, but there are some key differences between them. Here are a few of the most important differences:
Service offerings: AWS has the widest range of service offerings, followed by Azure and GCP. AWS offers services for everything from compute and storage to machine learning and artificial intelligence. Azure and GCP are more focused on specific areas, such as Azure for enterprise applications and GCP for machine learning.
Pricing: AWS is generally more expensive than Azure and GCP. However, AWS also offers a wider range of services, so you may be able to find the services you need for a lower price on AWS.
Ease of use: Azure is generally easier to use than AWS and GCP. This is because Azure is more tightly integrated with Microsoft products, which many businesses are already using.
Global reach: AWS has the widest global reach, followed by Azure and GCP. AWS has data centers located in more regions than Azure and GCP, which means that your data is always close to your users.
Comparison of services
AWS | Azure | GCP | |
---|---|---|---|
1. | Compute Services | ||
EC2 (Elastic Compute Cloud) | Virtual Machines (VMs) | Compute Engine | |
Lambda | Azure Functions | Cloud Functions | |
ECS (Elastic Container Service) | Azure Container Instances | Google Kubernetes Engine (GKE) | |
EKS (Elastic Kubernetes Service) | Azure Kubernetes Service (AKS) | Kubernetes Engine | |
2. | Storage Services | ||
S3 (Simple Storage Service) | Azure Blob Storage | Cloud Storage | |
EBS (Elastic Block Store) | Azure Managed Disks | Persistent Disk | |
EFS (Elastic File System) | Azure Files | Filestore | |
3. | Database Services | ||
RDS (Relational Database Service) | Azure SQL Database | Cloud SQL | |
DynamoDB | Azure Cosmos DB | Cloud Firestore, Cloud Spanner | |
Redshift | Azure Synapse Analytics (formerly SQL DW) | BigQuery | |
4. | Networking Services | ||
VPC (Virtual Private Cloud) | Virtual Network | Virtual Private Cloud (VPC) | |
ELB (Elastic Load Balancer) | Azure Load Balancer | Load Balancing | |
Route 53 | Azure DNS | Cloud DNS | |
5. | AI and Machine Learning Services | ||
Amazon SageMaker | Azure Machine Learning | AI Platform | |
Rekognition | Azure Cognitive Services | Cloud Vision, Cloud Natural Language, Cloud ML | |
AWS DeepLens | Azure Custom Vision | AutoML Vision, AutoML Natural Language, AutoML ML | |
6. | Serverless Services | ||
AWS Lambda | Azure Functions | Cloud Functions | |
API Gateway | Azure API Management | Cloud Endpoints | |
AWS Step Functions | Azure Logic Apps | Cloud Workflows | |
7. | Big Data and Analytics Services | ||
Amazon EMR | Azure HDInsight | Dataproc | |
Amazon Redshift | Azure Synapse Analytics (formerly SQL DW) | BigQuery | |
Amazon Kinesis | Azure Event Hubs, Azure Stream Analytics | Pub/Sub, Dataflow |