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How are AWS and Azure Different?

Microsoft Azure and Amazon Web Services (AWS) are renowned cloud service giants worldwide. Both service providers have introduced revolutionary changes in business operations by offering various services with flexibility and scalability. 

However, these services are somewhat different from each other, and their unique strengths and drawbacks. Various factors determine how these cloud platforms differ, including pricing, data availability rates, and many others.

Key Dissimilarities Between AWS and Azure

Some of the main differences between AWS and Azure are as follows –

Parameters Microsoft Azure AWS
Cloud Type
It is a virtual network.
It is a virtual private cloud.
Hybrid Cloud Support
It offers hybrid cloud support allowing businesses to join together onsite servers with cloud instances.
Not the best hybrid cloud support.
Government Cloud
Constrained scope for government cloud offerings.
Offers a threshold as far as government cloud aids.
Ecosystem
A small ecosystem with a few Linux options.
A software sphere with a wide-ranging partner ecosystem.
Networking Services
Includes automatic IP assignments, Azure content, load balancing, and endpoints defined in csdef/cscfg.
Includes Virtual Private Cloud, Elastic IP/ELB/ IP, ELB, Route 53, and Firewall heavily configurable.
Storage services
Include Azure Drive, Containers, Blob Storage, Storage Stats, Table Storage, and Tables.
Include AWS Import/Export, Domains, Buckets, EBS, SDB, SQS, and CloudFront
Deployment Services
Cspkg (fancy zip file), Coarse-grained updates “click to scale,” API via blob storage, Upload via the portal, or More magic.
Amazon Web Services, Traditional Deployment Models, Cloud Formation, Amazon Machine Instance (AMI), Elastic Beanstalk, Fine-grained updates.
Databases Services
MS SQL and SQL Sync
Oracle, My SQL, and DynamoDB
Big Data Support
Premium storage is suitable for big data. Standard storage can have problems with it.
Its EBS storage can handle big data.
Machine access
All machines are integrated into the cloud service. They respond to the same domain name having several ports.
It allows one to access each machine separately.
Security
Offer permissions on the whole account to ensure security.
Offers permission control features using defined roles to ensure security.
Long-term data archiving
No long-term data archiving or retrieval option is available.
Long-term data archiving or retrieval options available
Key features
Low cost, startup-friendly, and offers high performance.
Zero setups, Auto-scaling groups, Detail Monitoring.
Pricing models
2 pricing models - Per Minute and Free Trial
5 pricing models - Per Hour, Free Tier, no change for stopped, Free Trial Per Minute, and Pay for EBS volume.
Documentation
The documentation it provides is difficult to understand.
Offers extensive and informative documentation with services.
Ease of use
Organize users’ account details to store them in one location.
It has an easy-to-use and feature-rich interface.
Licensing and license mobility
It offers more SaaS options and is easily accessible to Windows administrators.
Offers highly flexible licenses with wide-ranging features.
Logging and monitoring
Azure ML Studio captures and tracks data ML-Flow.
AWS SageMaker records data over time and records model metrics using Cloud-Watch.
Open-source development
It is gradually opening support for open-source developers.
Ideal for Linux open-source software developers as it supports Linux and provides connectors for open-source apps.
Processes for deploying applications
Many ways are available to deploy apps, including app services, functions, batches, and cloud services, container services.
Need some host apps but offers services such as Batch, Lambda, Elastic Beanstalk, and container services.

Conclusion-

These are some key differences one can observe between these cloud services. Both have certain highlights and benefits but lack some other parameters. Thus, selecting any of these services depends on business requirements.