Difference between AWS, Azure and GCP
Difference between AWS, Azure, and GCP
Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) are all leading cloud computing platforms that provide a wide range of services for businesses of all sizes. Each platform offers similar capabilities such as compute, storage, and networking services, but they also have some key differences in terms of features, pricing, and ecosystem of tools and services.
AWS is the oldest and most mature of the three platforms, and it has the largest market share. It offers a wide range of services and is known for its flexibility and scalability. AWS has a large and active ecosystem of partners and customers, and it offers a wide range of tools and services that integrate with its core offerings.
Azure is Microsoft’s cloud platform and it is known for its strong integration with other Microsoft products and services, such as Active Directory and Visual Studio. Azure also has a large and growing ecosystem of partners and customers, and it offers a wide range of tools and services that integrate with its core offerings.
GCP is Google’s cloud platform and it is known for its strong focus on data analytics and machine learning. GCP also offers a wide range of services and is known for its strong integration with other Google products and services, such as Google Analytics and Google BigQuery. GCP also has a large and growing ecosystem of partners and customers, and it offers a wide range of tools and services that integrate with its core offerings.
Amazon Elastic Compute Cloud (EC2) is a service offered by Amazon Web Services (AWS) that allows users to rent virtual computers on which to run their own applications. Azure Virtual Machines (VMs) is a service offered by Microsoft Azure that allows users to create and manage virtual machines in the Azure cloud. Google Compute Engine (GCE) is a service offered by Google Cloud Platform (GCP) that allows users to create and run virtual machines on Google’s infrastructure.
All three services offer similar capabilities, such as the ability to create and manage virtual machines and provide a variety of operating systems and configurations to choose from. However, there are some differences in pricing, features, and the ecosystem of tools and services that each provider offers. It’s recommended to evaluate the specific requirements of your use case and compare the features and pricing of each service before making a decision.
Feature | Amazon EC2 | Azure Virtual Machines | Google Compute Engine |
---|---|---|---|
Provider | AWS | Azure | GCP |
Virtual Machine Types | A variety of instance types with different combinations of CPU, memory, storage, and networking capacity. | A variety of instance types with different combinations of CPU, memory, storage, and networking capacity. | A variety of instance types with different combinations of CPU, memory, storage, and networking capacity. |
Operating Systems | Linux, Windows | Linux, Windows, and others | Linux, Windows, and others |
Auto-scaling | Yes | Yes | Yes |
Load Balancing | Yes | Yes | Yes |
Networking options | VPC, Direct Connect, Elastic IPs | Virtual Network, ExpressRoute, Load Balancer | VPC, Cloud VPN, Cloud Router, Cloud Interconnect |
Integration with other services | A wide range of services such as RDS, Elasticache, S3, and more are available. | A wide range of services such as SQL Database, Storage, and more are available. | A wide range of services such as SQL, Storage, and more are available. |
Pricing | Pay-as-you-go, reserved instances, and spot instances | Pay-as-you-go, reserved instances, and spot instances | Pay-as-you-go, sustained use discounts, and committed use discounts |
Platform as a Service (PaaS) is a cloud computing model that provides users with a platform to develop, run, and manage applications without the need to handle underlying infrastructure.
Amazon Web Services (AWS) offers a PaaS service called Elastic Beanstalk, which allows developers to easily deploy, run, and scale web applications and services. It supports a variety of programming languages and frameworks, including Java, .NET, PHP, Node.js, Python, Ruby, and Go.
Azure PaaS provides a platform for building, deploying, and scaling web applications, mobile apps, and integration services. Azure App Service is a fully managed platform for building, deploying, and scaling web apps. Azure Functions is a serverless compute service that enables you to run code on-demand without having to provision or manage infrastructure.
Google Cloud Platform (GCP) offers a PaaS service called Google App Engine, which allows developers to build and run applications on the same infrastructure that powers Google’s own applications. It supports a variety of programming languages and frameworks, including Java, Python, PHP, and Go. GCP also provides Cloud Functions, a serverless compute service that allows developers to run code without provisioning or managing servers.
Feature | AWS Elastic Beanstalk | Azure PaaS | GCP PaaS |
---|---|---|---|
Provider | Amazon Web Services | Microsoft Azure | Google Cloud Platform |
Programming languages supported | Java, .NET, PHP, Node.js, Python, Ruby, Go | .NET, Java, Node.js, PHP, Python, Ruby | Java, Python, PHP, Go, Node.js |
Frameworks supported | A variety of frameworks are supported | A variety of frameworks are supported | A variety of frameworks are supported |
Auto-scaling | Yes | Yes | Yes |
Load Balancing | Yes | Yes | Yes |
Networking options | VPC, Direct Connect, Elastic IPs | Virtual Network, ExpressRoute, Load Balancer | VPC, Cloud VPN, Cloud Router, Cloud Interconnect |
Integration with other services | A wide range of services such as RDS, Elasticache, S3, and more are available. | A wide range of services such as SQL Database, Storage, and more are available. | A wide range of services such as SQL, Storage, and more are available. |
Please note that this table is not an exhaustive list of all the features and capabilities of each PaaS service, and the specific features and capabilities of each service may vary. It’s recommended to evaluate the specific requirements of your use case and compare the features of each service before making a decision.
All three major cloud providers, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) offer a wide range of storage and database services.
AWS offers services such as Amazon Simple Storage Service (S3) for object storage, Amazon Elastic Block Store (EBS) for block storage, and Amazon Relational Database Service (RDS) for relational databases. It also offers Amazon DynamoDB for NoSQL databases, Amazon Redshift for data warehousing, and Amazon Elastic File System (EFS) for file storage.
Azure offers services such as Azure Blob Storage for object storage, Azure Disk Storage for disk storage, and Azure SQL Database for relational databases. It also offers Azure Cosmos DB for NoSQL databases, Azure Data Lake Storage for data lake storage, and Azure File Storage for file storage.
GCP offers services such as Google Cloud Storage for object storage, Persistent Disk for block storage, and Cloud SQL for relational databases. It also offers Cloud Bigtable for NoSQL databases, BigQuery for data warehousing, and Filestore for file storage.
Feature | Azure | GCP | AWS |
---|---|---|---|
Provider | Microsoft Azure | Google Cloud Platform | Amazon Web Services |
Object Storage | Azure Blob Storage | Cloud Storage | Amazon S3 |
Block Storage | Azure Disk Storage | Persistent Disk | Amazon EBS |
Relational Database | Azure SQL Database | Cloud SQL | Amazon RDS |
NoSQL Database | Azure Cosmos DB | Cloud Bigtable | Amazon DynamoDB |
Data Warehousing | Azure Data Lake Storage | BigQuery | Amazon Redshift |
File Storage | Azure File Storage | Filestore | Amazon Elastic File System |
Please note that this table is not an exhaustive list of all the features and capabilities of each storage and database service, and the specific features and capabilities of each service may vary. It’s recommended to evaluate the specific requirements of your use case and compare the features of each service before making a decision.
AWS offers Amazon Elastic File System (EFS) which is a fully-managed service that makes it easy to set up, scale, and run file storage in the AWS Cloud. It supports NFS protocols and can be accessed concurrently by multiple Amazon Elastic Compute Cloud (EC2) instances.
Azure offers Azure Files which is a fully managed, cloud-based file share that allows users to access files using the standard SMB protocol. It supports both NFS and SMB protocols, can be accessed concurrently by multiple virtual machines and supports data tiering with Azure File Sync.
GCP offers Filestore, a fully-managed file storage service that allows users to create and manage NFS and SMB-based file shares that can be accessed concurrently by multiple VMs. It supports automatic data tiering, automatic data replication, and automatic data backup.
Feature | Azure Files | GCP Filestore | AWS Elastic File System (EFS) |
---|---|---|---|
Provider | Microsoft Azure | Google Cloud Platform | Amazon Web Services |
Protocol supported | SMB and NFS | NFS and SMB | NFS |
Concurrent access | Yes | Yes | Yes |
Automatic data tiering | Yes (Azure File Sync) | Yes | No |
Automatic data replication | Yes | Yes | Yes |
Automatic data backup | Yes | Yes | No |
Please note that this table is not an exhaustive list of all the features and capabilities of each file storage services, and the specific features and capabilities of each service may vary. It’s recommended to evaluate the specific requirements of your use case and compare the features of each service before making a decision.
AWS offers services such as Amazon SageMaker for machine learning, Amazon Transcribe for speech
Feature | Azure Specialized Services | GCP Specialized Services | AWS Specialized Services |
---|---|---|---|
Provider | Microsoft Azure | Google Cloud Platform | Amazon Web Services |
Machine Learning | Azure Machine Learning | Google AI Platform | Amazon SageMaker |
Speech-to-text | Azure Speech Services | Cloud Speech-to-Text | Amazon Transcribe |
Text-to-speech | Azure Cognitive Services | Cloud Text-to-Speech | Amazon Polly |
Computer Vision | Azure Computer Vision | Cloud Vision | Amazon Rekognition |
Natural Language Processing | Azure Cognitive Services | Cloud Natural Language | Amazon Comprehend |
Internet of Things (IoT) | Azure IoT Hub | Cloud IoT | AWS IoT |
Blockchain | Azure Blockchain Service | Cloud Blockchain | Amazon Managed Blockchain |
Please note that this table is not an exhaustive list of all the specialized services that are offered by each provider and the specific features and capabilities of each service may vary. It’s recommended to evaluate the specific requirements of your use case and compare the features of each service before making a decision.
AWS, Azure, and GCP all provide client libraries, SDKs, and command-line interfaces (CLIs) to interact with their respective cloud services. These clients allow developers to write code in various programming languages to access and manage cloud resources.
Feature | AWS Clients | Azure Clients | GCP Clients |
---|---|---|---|
Provider | Amazon Web Services | Microsoft Azure | Google Cloud Platform |
Programming languages supported | multiple languages such as Java, .NET, Python, Ruby, C++ and more | multiple languages such as .NET, Java, Python, Go and more | multiple languages such as Java, .NET, Python, Go, Node.js and more |
SDKs | AWS SDKs | Azure SDKs | Google Cloud SDKs |
CLI | AWS CLI | Azure CLI | gcloud CLI |
Integration with other tools | AWS tools such as AWS CloudFormation, AWS CloudTrail, and AWS Elastic Beanstalk | Azure tools such as Azure DevOps, Azure Monitor, and Azure Automation | GCP tools such as Cloud Deployment Manager, Stackdriver, and Cloud SDK |
Companies like Netflix, Spotify, and Airbnb use AWS for their infrastructure. Microsoft Azure is used by companies like GE, Honeywell, and DuPont. GCP is used by companies like Spotify, Best Buy, and HSBC. But it’s worth noting that many companies also use other cloud providers such as Oracle, Alibaba Cloud, and IBM Cloud