Azure vs AWS Pricing: A Comprehensive Comparison | Code Boost
Description: While factors like performance, reliability, and features are important when choosing a cloud provider, cost over time is often a top concern. Two giants dominate the cloud computi...

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# Azure vs AWS Pricing: A Comprehensive Comparison

By Matt · Aug 8, 2024

While factors like performance, reliability, and features are important when choosing a cloud provider, cost over time is often a top concern. Two giants dominate the cloud computing landscape: Microsoft Azure and Amazon Web Services (AWS). Both offer a wide array of services, but their pricing models can differ significantly.

In this comprehensive blog post, we'll delve into the intricacies of Azure vs. AWS pricing, compare their various services, and highlight potential cost-saving strategies.

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# Azure vs AWS Pricing

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### Comparing Compute Costs

Compute resources, like virtual machines (VMs), are a fundamental building block of cloud infrastructure. Let's compare the on-demand and reserved instance pricing for some common VM types in the US East region:

#### On-Demand Instance Pricing Comparison (US East):

Instance Type | Azure VM (Price per Hour) | AWS EC2 (Price per Hour)
--- | --- | ---
General Purpose |  |
- Small (e.g., B1s) | ~$0.012 | ~$0.0116 (t4g.micro)
- Medium (e.g., B2s) | ~$0.046 | ~$0.0464 (t3.medium)
Compute Optimized |  |
- Small (e.g., F2s) | ~$0.085 | ~$0.0856 (c5.large)
- Medium (e.g., F4s) | ~$0.17 | ~$0.1712 (c5.xlarge)
Memory Optimized |  |
- Small (e.g., E2s) | ~$0.067 | ~$0.0770 (r5.large)
- Medium (e.g., E4s) | ~$0.134 | ~$0.1540 (r5.xlarge)

As you can see, on-demand instance pricing is quite comparable between Azure and AWS for similar instance types. However, specific use cases may favor one platform over the other due to differences in underlying hardware and features.

#### Reserved Instance Pricing Comparison (US East, 1-Year Term):

Instance Type | Azure VM (1-Year Reserved Price per Hour) | AWS EC2 (1-Year Reserved Price per Hour)
--- | --- | ---
General Purpose |  |
- Small (e.g., B1s) | ~$0.009 | ~$0.007 (t4g.micro)
- Medium (e.g., B2s) | ~$0.034 | ~$0.030 (t3.medium)
Compute Optimized |  |
- Small (e.g., F2s) | ~$0.064 | ~$0.051 (c5.large)
- Medium (e.g., F4s) | ~$0.128 | ~$0.102 (c5.xlarge)
Memory Optimized |  |
- Small (e.g., E2s) | ~$0.051 | ~$0.046 (r5.large)
- Medium (e.g., E4s) | ~$0.102 | ~$0.092 (r5.xlarge)

###

Reserved instances offer substantial discounts, but Azure requires full upfront payment for the term, while AWS provides more flexible payment options with varying discount levels. Consider your cash flow and usage predictability when choosing between on-demand and reserved instances.

### Comparing Storage Costs

Both Azure and AWS offer a range of storage options, each with different pricing structures. Here's a comparison of their object storage pricing for standard, infrequent access, and archive tiers:

#### Object Storage Pricing Comparison (US East):

Storage Tier | Azure Blob Storage Price (per GB) | Amazon S3 Price (per GB)
--- | --- | ---
Frequent Access |  |
- First 50 TB | ~$0.0184 | ~$0.023
- 51-500 TB | ~$0.0177 | ~$0.022
Infrequent Access |  |
- Standard IA | ~$0.0125 | ~$0.0125
Archive Storage |  |
- Archive | ~$0.0010 | ~$0.004

Object storage pricing is quite similar between the two providers, with minor differences in some tiers. However, AWS's Glacier Deep Archive storage class is significantly cheaper than Azure's Archive tier for long-term archival.

For block storage, both providers offer various types of SSDs and HDDs with different performance characteristics and pricing.

### Understanding Cloud Pricing Models

- Pay-As-You-Go: This model allows you to pay only for the resources you actually consume, providing flexibility for fluctuating workloads.
- Reserved Instances (RIs): RIs offer significant discounts compared to on-demand pricing when you commit to using specific resources for a one- or three-year term.
- Spot Instances: These are spare compute instances available at a lower cost but can be interrupted with short notice, making them ideal for flexible workloads.
- Savings Plans (AWS only): AWS Savings Plans offer a flexible way to save on compute usage with a commitment to a consistent amount of usage for one or three years.

Additionally, cloud pricing is multi-dimensional, encompassing costs for compute, storage, data transfer, and various other services. Understanding these dimensions is key to accurately assessing your cloud infrastructure's total cost of ownership (TCO).

### Other Cost Considerations

Beyond compute and storage, several other factors can impact your overall cloud spending:

- Data Transfer: Outbound data transfer from the cloud typically incurs charges, while inbound data transfer is usually free.
- Additional Services: Costs for databases, analytics tools, machine learning services, and other offerings can vary significantly between providers.
- Support Plans: Different levels of support are available at different price points.
- Regional Pricing Differences: Prices can fluctuate depending on the region where your resources are deployed.

### Tips for Optimizing Cloud Costs

Regardless of the cloud provider you choose, there are several strategies to optimize your cloud spending:

- Rightsize Resources: Choose the right instance types and storage options to match your workload requirements and avoid overprovisioning.
- Utilize Reserved Instances/Savings Plans: If you have predictable workloads, committing to reserved instances or savings plans can lead to substantial savings.
- Leverage Spot Instances: For fault-tolerant workloads, spot instances can significantly reduce costs.
- Monitor Usage: Regularly monitor your cloud usage to identify inefficiencies and optimize resource allocation.
- Use Cost Management Tools: Both Azure and AWS offer cost management tools to track spending, identify trends, and forecast future costs.

### Conclusion

The Azure vs. AWS pricing debate is nuanced, with no one-size-fits-all answer. Both cloud services offer a wide array of services with diverse pricing models. The best choice for you will depend on your specific needs, workload characteristics, and budget constraints.