AWS vs. Azure vs. Google Cloud Comparison 2019

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COMPUTE SERVICES

EC2

Virtual Machines

Compute Engine

Elastic Container Service

Virtual Machine Scale Sets

Kubernetes

Elastic Container Service for

Azure Container Service

Functions

Kubernetes

(AKS)

Container Security

Elastic Container Registry

Container Instances

Graphics Processing Unit

Lightsail

Batch

(GPU)

Batch

Service Fabric

App Engine

Cloud Services

Knative

Elastic Beanstalk Fargate

STORAGE SERVICES

Simple Storage Service (S3)

Blob Storage

Cloud Storage

Elastic Block Storage (EBS)

Queue Storage

Persistent Disk

Elastic File System (EFS)

File Storage

Transfer Appliance

Storage Gateway

Disk Storage

Transfer Service

Snowball

Data Lake Store

Snowball Edge Snowmobile

MACHINE LEARNING

SageMaker

Machine Learning

Cloud Machine Learning Engine

AML Apache MXNet on AWS TensorFlow on AWS

STRENGTHS

Dominant market position

Second largest provider

Designed for cloud-native

Extensive, mature offerings

Integration with Microsoft

businesses

Support for large organizations

tools and software

Commitment to open

Extensive training

Broad feature set

source and portability

Hybrid cloud

Deep discounts and

Support for open source

flexible contracts

Global reach

DevOps expertise

WEAKNESSES

Difficult to use

Issues with documentation

Cost management

Incomplete management

Overwhelming options

tooling

Late entrant to IaaS market Fewer features and services Historically not as enterprise focused

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