Azure and AWS both deliver, but the right fit depends on your priorities. This guide breaks down the core differences to help you decide.

Cloud infrastructure is now the backbone of digital transformation, and choosing the right provider, whether Microsoft Azure or AWS, is an important technology decision.

Microsoft Azure and Amazon Web Services provide almost identical computing, storage, databases, and analytics services. However, they take different approaches to pricing, integration, and hybrid cloud. This makes comparison essential, especially for IT leaders who want to align cloud strategy with business goals.

Whether you're migrating from legacy infrastructure or scaling a new product, understanding the tradeoffs is critical.

At a glance: Microsoft Azure vs AWS

That was the quick take. Now, let’s dig into the details to help you determine which platform best suits your needs.

Cost and pricing: Microsoft Azure vs AWS

Cloud pricing models can be complex, and both AWS and Azure have various approaches to billing, discounts, free tiers, and data transfer costs.

Compute pricing

Both AWS and Azure provide on-demand pricing and discounts for long-term commitments. AWS Reserved Instances and Savings Plans allow cost savings of up to 70% for 1 or 3-year commitments. Spot Instances provide cost savings of up to 90% on interruptible workloads.

Free tiers

Both Azure and AWS provide free tiers and trial credits. AWS provides up to $200 in credits to use on major services for up to 6 months. On the other hand, Azure provides a $200 credit for the first 30 days, 12 months of popular services, and 65+ always-free services.

Data transfer (egress)

On Azure, inbound data transfer is free. Data egress (outbound) varies by region, with transfers within regions in North America and Europe being the cheapest at $0.02/GB and South America the most expensive at $0.16/GB. Internet egress is free for the first 100GB/month, with other costs ranging from $0.087/GB to $0.181/GB for the next 10TB.

AWS does not change inbound data transfer in all regions. Data transfer to the internet costs $0.09/GB for the first 10 GB, which reduces with higher usage. However, data transfer across regions costs $0.01/GB.

Storage costs

AWS S3 has multiple storage tiers and charges for data stored and requests. The S3 standard tier starts at $0.023/GB per month for US regions for the first 50TB/month. The most inexpensive tier is the Glacier Deep Archive, which costs $0.00099/GB per month.

Azure blob storage consists of the Hot, Cool, and Archive tiers. Hot has the highest storage cost, starting at $0.15/GB for the first 50TB/month, while Archive is the lowest cost, starting at $0.0002/GB per month for a similar amount of data. Azure also provides Premium Blob Storage, which provides consistently low latency but with high transaction costs.

Database costs

Azure SQL Databases costs $5/month for 2B, while the AWS RDS costs $0.017/hour.

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Compute: Microsoft Azure vs AWS

AWS has EC2 as its most popular compute service, while Azure has Azure Virtual Machines. Both of these services provide comparable functionality and have a wide range of VM instance types for various needs:

Instance types

AWS offers a broader selection of instance families optimized for memory compute, general-purpose, FPGA, and GPU. It also offers custom options like the Graviton ARM-based processors, which provide better performance and price, and the Nitro architecture for near bare-metal I/O.

Azure has comparable instances, such as the A-series, D-series, E-series, H-series (for HPC), and NV/ND for GPUs.

Scaling and availability

Azure and AWS use multiple availability zones in many regions for high availability. Azure provides Availability Sets for grouping VMs to ensure they are spread across fault domains within a data center, and AWS enables developers to launch instances in multiple Availability Zones within a region.

Serverless compute

Azure Functions is a serverless service for running code snippets in a fully managed environment. In contrast, AWS Lambda runs code in response to events without any server management. Lambda supports more runtime languages natively, although Azure Functions can run a variety of languages, and also with an on-premise option.

Containers and orchestration

For containerized workloads, you can use the Azure Kubernetes Service (AKS), which is integrated within the Azure CLI and portal. The Azure Container Instances (ACI) can run single containers on demand, while the Azure Red Hat OpenShift is a handy option for those who prefer the Red Hat Kubernetes distro.

AWS offers the Amazon Elastic Kubernetes Service (EKS) to run Kubernetes on AWS with heavy lifting, or the Amazon Elastic Container Service (ECS) for cluster management.

Storage: Microsoft Azure vs AWS

If you need single-AZ, micro-latency object access, evaluate S3 Express One Zone on AWS. Azure’s Container Storage (GA) might be the most suitable if you want simpler container-native volumes with centralized management.

Azure Storage includes:

• Blob Storage for objects
• File Storage for files
• Table Storage for NoSQL key-value storage
• Queue Storage for message queuing

Azure Blob Storage, which is most comparable to Amazon S3, provides the following storage tiers:

• Hot
• Cool
• Cold
• Archive
• Premium

Amazon S3 is the main object storage service for AWS. It also offers the following:

• Standard for frequently accessed data
• Standard-Infrequent Access for rapid data access whenever needed
• One Zone-Infrequent Access for infrequently accessed data
• Intelligent-Tiering for automatic data movement to cost-effective access tiers
• Express One Zone for storing frequently accessed data in latency-sensitive applications
• Glacier Instant Retrieval for archival data that might require fast retrieval
• Glacier Deep Archive for long-term archiving
• Glacier Flexible Retrieval for archival data accessed 1-2 times a year and retrieved asynchronously.

AWS also provides the Elastic Block Store (EBS) for EC2 instances, which provides persistent storage volumes, and the Amazon Elastic File System (EFS) for network file storage.

Bottom line on storage:

Choose AWS if you need more granular storage and specialized options, or Azure for simple tiering and integrated storage types under the Microsoft umbrella.

Services: Microsoft Azure vs AWS

Both Azure and AWS have over 200+ cloud-based products and services, each with some differing approaches:

Database

Azure focuses on managed services designed for deep integration with Microsoft software and hybrid environments. It provides managed relational databases such as Azure SQL Database (for SQL Server compatibility), Azure Database for PostgreSQL, and Azure Database for MySQL. For NoSQL, the Azure Cosmos DB multi-model database service.

AWS has multiple database services, such as Amazon Aurora for relational storage and Amazon DynamoDB for key-value storage. RDS supports several engines (PostgreSQL, MariaDB, MySQL, and SQL Server, giving you more flexibility.

AI/ML

Azure’s AI services tie into Azure AI Studio with services such as Azure OpenAI Service (which provides GPT models as a service). Azure has the upper hand in AI services, with OpenAI being a differentiator. Besides, the Azure Machine Learning Studio has a drag-and-drop model that provides both low-code and code-first experiences.

AWS has similar services, such as Amazon Rekognition for image recognition, Comprehend (NLP), and Polly for text-to-speech. It also enables ML Ops through AWS SageMaker, which simplifies and accelerates the machine learning lifecycle.

IoT and developer tools

Azure is particularly strong on IoT use cases, thanks to services like the Azure IoT Hub, which provides a central hub for IoT management, and the Azure IoT Edge, which extends the IoT Hub to edge devices.

Security: Microsoft Azure vs AWS

While both Azure and AWS have a shared responsibility model, they have different security approaches:

Identity and access management

Azure uses the Azure Active Directory (Azure AD), which is part of the Microsoft Entra, for SSO and cloud and hybrid identity. It’s deeply integrated with on-premise Active Directory, Windows, and Microsoft 365. In contrast, AWS uses Identity and Access Management (IAM) for fine-grained, policy-based control.

Data encryption and key management

The Azure Key Vault manages encryption keys, certificates, and secrets, while AWS leverages the Key Management Service (KMS) and the CloudHSM for dedicated hardware security. Both support “bring your own key” (BYOK) and HSM, but Azure Key Vault is often more tightly integrated with identity and enterprise compliance needs, while AWS KMS is tightly coupled to AWS resource policies.

Threat detection and security monitoring

AWS comes with Amazon GuardDuty to detect threats, while Azure uses Microsoft Defender for Cloud and Sentinel, providing a more unified hybrid/multi-cloud security posture.

Performance: Microsoft Azure vs AWS

AWS continuously designs custom hardware for performance. The Nitro System offloads networking and storage tasks to dedicated Nitro cards, enabling EC2 instances to achieve near-bare-metal performance.

AWS also designs the Graviton series CPUs, which provide excellent performance for compute-intensive workloads, and custom AI chips (Trainium and Inferential) for ML acceleration.

Azure leverages FPGA acceleration in its network to speed up AI processing and networking, alongside custom Nvidia GPUs for high-performance computing.

Azure has 60+ geographical locations, meaning you can deploy resources in a location physically closer to your end-users. However, AWS has more Availability Zones (AZs) per region, 400+ CloudFront edge locations, and 10+ regional edge cache locations. While both deliver excellent global performance, you have to consider Azure Edge Zones or AWS Local Zones in the target area.

Azure’s custom hardware gives it an edge in raw compute and low-level optimizations, with the integration of acceleration enabling it to perform better for certain workloads and geographical locations.

Documentation and support: Microsoft Azure vs AWS

Each platform provides extensive documentation and multiple support plan options, but there are some major differences.

Documentation quality

AWS has comprehensive documentation, detailed developer guides and API references, and reference architectures and whitepapers. Users can also find answers in the Knowledge Center.

Azure provides documentation through Azure Docs and Microsoft Learn, which includes tutorials and code snippets. However, AWS is more organized and exhaustive, which gives it an edge.

Support plans

AWS and Azure have comparable support plans, although Azure offers the Professional Direct tier for faster responses. Microsoft’s support channels are more approachable, and AWS support is more reliable in the enterprise tier.

Solution architects and partner support

AWS has AWS Solutions Architects and TAMs for enterprise customers and consultants, as most cloud consultants specialize in this area. On the other hand, Azure has a vast network of Microsoft partners and MSPs.

Hybrid and multi-cloud support: Microsoft Azure vs AWS

Both Azure and AWS have distinct hybrid and multi-cloud approaches:

Hybrid approach

Azure is highly focused on hybrid cloud capabilities, which enable customers with on-premises infrastructure to adopt the cloud. Azure Arc allows you to project on-premise and even other cloud resources, such as AWS and GCP, into the Azure plane. Besides, you can use the Azure Stack Edge, Azure Stack Hub, and Azure Stack HCI to run Azure services consistently at your own data center.

AWS is more focused on cloud-native offerings. However, the introduction of AWS Outposts enables you to extend your AWS infrastructure and services to on-premises locations.

Multi-cloud management

Unlike Azure, which has the Arc, AWS does not have an equivalent single-pane multi-cloud management tool. However, it has the AWS Migration Hub to track migrations from other cloud platforms.

When to use Microsoft Azure

Below are some situations where Microsoft Azure shines:

• Industrial IoT: Azure is a leading provider of IoT, enabling users to build and manage IoT solutions. It leverages services such as the Azure IoT Hub, Azure IoT Edge, and Azure Time Series Insights.
  
  Healthcare, manufacturing, and construction companies use Azure IoT to monitor devices and collect data. Azure IoT Edge extends analytics to edge devices and allows the deployment of AI workloads directly on IoT devices. All these services provide a unified platform for managing a wide range of IoT solutions.

• Regulated industries: Azure maintains a strong compliance portfolio to help organizations meet compliance in heavily regulated industries. Healthcare, government, and finance companies can use Azure to maintain data privacy through secure deployments and security practices.
  
  Microsoft for Sovereignty enables organizations to build upon Azure’s public offerings and meet specific compliance requirements.

• Enterprises with a Microsoft footprint: Organizations heavily using Microsoft software and other services like Windows and Microsoft 365 can benefit from Azure’s integration. Azure connects to on-premise AD for SSO, and you can also use existing Windows Server licenses with Azure Hybrid Benefit for cost savings.
  
  Developers using VS Code and Microsoft-backed frameworks like ASP.NET find it easy to use Azure tooling and deploy apps to Azure with minimal effort.

• Data analytics with Microsoft integration: Organizations using Microsoft-native tools like Excel, SQL Server, or Power BI can use Azure to keep data close to those services. Azure Synapse Analytics integrates with Azure Machine Learning and Power BI to speed up the development of analytic solutions.

When to use AWS

Here are scenarios under which AWS is most suitable:

• High-performance computing (HPC) and specialized workloads: AWS is suitable for workloads that require extreme performance. These include computational fluid dynamics, deep learning workloads, genomic analysis, weather modeling, and geoscientific simulations. Providing HPC-optimized instances and specialized HPC chips and GPUs gives AWS an edge.

• Global reach with low latency. AWS has a vast global infrastructure that is continuously expanding. It has almost 40 regions and 100+ AZs. AWS is most suited for applications that need ultra-low latency to end users globally. It provides many tools to achieve that, such as AWS CloudFront, Route 53, and Local Zones. You can deploy edge servers in many cities via Local Zones and leverage their global network for network delivery.

• Fault-tolerant workloads and availability. AWS replicates data across multiple AZs to ensure maximum availability. It also leverages services like Auto Scaling for scaling virtual machines and Elastic Load Balancing to distribute traffic to multiple servers for better performance.

• Extensive data analytics and big data: AWS provides powerful tools for big data operations such as processing, search, business intelligence, and streaming. For example, Amazon Elastic MapReduce (EMR) enables log analysis, data warehousing, and web indexing capabilities. Other services include Amazon Redshift for large-scale warehousing and S3 for storage.

How Fivetran supports cloud data extraction across Azure and AWS

There’s no clear winner or universally better platform. Choosing between Azure and AWS is about aligning with your business’s architecture, governance, and goals. Both deliver comprehensive, secure ecosystems, global infrastructure, and a deep catalog of services.

Whether you prefer Azure or AWS, Fivetran provides a single, automated path for your data sources so teams can deliver faster.

• On Azure, it connects to Azure SQL Database or Synapse, writes tables on the target schema, handles schema drifts automatically, and loads into data lakes like Blob Storage.
• On AWS, it auto-creates target schemas and tables, and optimizes batch loads for slot efficiency. You can configure S3 buckets and prefixes, apply configurations, and move data to Redshift, Athena, or other transformations.

Regardless of your cloud strategy, Fivetran can simplify the process and keep your data flowing reliably, securely, and with minimal overhead.

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Frequently asked questions

Which is better: Microsoft Azure or Amazon Web Services?

There is no inherently better cloud platform between Azure and AWS. The optimal choice depends on the existing technology stack, talent pool, and strategic business priorities. Regardless of which tool you use, the performance and services provided are highly comparable. Consider specific workloads and cost implications.

Can I use both AWS and Azure together?

Yes, companies can use Azure and AWS together in a multi-cloud strategy. This approach allows you to combine each provider's unique strengths and mitigate challenges such as vendor lock-in. For example, you can use AWS for its specialized data analytics offerings alongside Azure for its Microsoft-native integration.

Which cloud provider is better for a hybrid cloud setup?

Azure exhibits a strong focus on hybrid due to its deep integration with Microsoft’s on-premise technologies, such as Microsoft 365, Active Directory, and Windows Server. It also has services that extend cloud capabilities to on-premises, such as Azure Stack, Azure Arc, and Azure Edge. While AWS has advanced significantly with AWS Outposts, Azure has a comprehensive suite of tools and a historical edge.