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Cloud pricing comparison: choosing the right cloud provider
Choosing the right cloud service provider requires careful consideration due to the vast array of options, each with unique features and capabilities. Pricing significantly influences the decision, as organizations strive to balance their requirements with their budget to find the perfect fit.
In this article, we provide an overview of the prices for computing and storage services provided by the global cloud giants—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Provider (GCP). Please note that the prices discussed below are current as of June 2024.
Top three cloud providers
AWS, Azure, and GCP are three of the leading cloud service providers, together holding a 66% market share in the worldwide cloud infrastructure market as of the fourth quarter of 2023. Amazon is the leader with a 31% market share, followed by Microsoft with 24% and Google with 11%.
Source: Statista
Each giant offers over 200 services tailored to various computing needs, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) solutions. Although these cloud providers may seem interchangeable at first glance, each has unique strengths and challenges that affect the overall cost and experience.
AWS, launched in 2006, is recognized for its extensive service catalog and vast worldwide network, making it a favored choice for organizations looking to scale globally. Its maturity and reliability are well-established, backed by years of operational experience and a broad customer base. AWS offers a comprehensive set of tools for developers, extensive computing services, and a robust ecosystem for Internet of Things (IoT), machine learning (ML), and artificial intelligence (AI) applications.
Azure, launched in 2010, integrates seamlessly with Microsoft’s software offerings, making it a compelling choice for organizations already reliant on products like Windows Server, Active Directory, and Office 365. In addition to its robust hybrid cloud capabilities, which allow companies to bridge their on-premises infrastructure with the cloud, Azure supports fully cloud-based solutions that can be built from the ground up.
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Explore our expertiseAzure also boasts a strong focus on enterprise needs, offering extensive support for various programming languages, frameworks, and tools preferred by businesses.
Launched in 2011, GCP is the youngest among the three giants, distinguishing itself with leading data management and data analytics technologies. Its expertise in these areas makes GCP an appealing option for organizations that rely heavily on big data and machine learning. GCP’s commitment to open standards and open-source projects makes it an appropriate choice for developers seeking flexible and innovative cloud environments.
| AWS | Microsoft Azure | GCP | |
|---|---|---|---|
| Launch year | 2006 | 2010 | 2011 |
| Regions | 33 | 60 | 40 |
| Services | >200 | >200 | >100 |
| Pricing models | Pay-as-you-go, Saving Plans, Dedicated Hosts, Reserved Instances, Dedicated Hosts | Pay-as-you-go, Saving Plan, Reserved Instances, Hybrid Benefit, Spot Instances, Azure Dev/Test | Pay-as-you-go, Committed Use |
| Free period | Yes | Yes | Yes |
| Major strengths | Extensive infrastructure | Seamless integration with Microsoft products | Strong data analytics and machine learning |
| Challenges | High complexity in service configurations and options | Complex security configurations, especially with hybrid cloud scenarios | Complexity in integrating with non-Google services, fewer features in some areas compared to AWS and Azure |
| Supported OS | Linux, macOS, Windows Server | Windows Server, Linux | Linux, Windows Server |
| Max memory in virtual machines | 24 TiB | 11.4 TiB | 10.9 TiB |
All three cloud providers offer more or less the same services, including computing, storage, networking, and more. Apart from their strengths and challenges, AWS, Azure, and GCP differ in costs, which vary from project to project. We suggest examining the pricing models to identify opportunities for cost optimization, followed by a comparison of prices for compute instances and storage.
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Pricing models
The pricing models provided in this section are mainly applicable to virtual servers. The method of calculating costs may be different for other services.
AWS
Depending on the product, AWS has the following pricing models:
- On-demand. You pay only for the services you use, with no long-term commitments or up-front payments. Prices are typically charged on a per-hour or per-second basis.
- Reserved instances (RIs). In exchange for committing to a specific amount of computing capacity for a one- or three-year term, this model offers a significant discount (up to 75%) compared to on-demand pricing. This makes RIs suitable for predictable workloads.
- Savings plans (SPs). Similar to RIs, SPs offer discounts in exchange for committing to a consistent amount of usage (measured in dollars per hour) for a one- or three-year term. However, SPs are more flexible than RIs, allowing you to switch between instances across different families, operating systems, and AWS regions.
- Spot instances (SIs). SIs allow you to utilize available unused computing capacity in the AWS cloud at discounts of up to 90% off the standard on-demand prices. This is an ideal option for stateless and fault-tolerant solutions like big data, CI/CD, containerized workloads, and web servers.
AWS also offers a free tier, which includes trials for new customers and services that are always free up to certain limits.
AWS Pricing Models
| On-demand | RI | SP | SI | |
|---|---|---|---|---|
| Commitment | – | 1 or 3 years | 1 or 3 years | – |
| Up-front costs | – | + | + | – |
| Benefit | Highly flexible | Cheaper than on-demand | Predictable cost, cheaper than on-demand, more flexible than RI | Cheapest option |
| Limitation | Expensive in the long run | Limited flexibility | Applies to a limited number of services | Can be terminated at any time with little notice, limited flexibility |
| Best for | Short-term projects | Predictable apps | Predictable apps | Stateless and fault-tolerant apps |
Azure
Azure’s pricing models include:
- Pay-as-you-go. You pay for what you use without any up-front commitment. Prices are billed by minute or by second, depending on the service. This model offers the flexibility to start and stop services at any time and only pay for actual usage, making it ideal for projects with variable workloads.
- Reservations. For predictable workloads and long-term projects, reserving instances for one or three years can help businesses reduce costs by up to 72% compared to the pay-as-you-go model. Cancellation is possible for a fee.
- Spot pricing. You can bid on unused Azure capacity at a rate that is discounted up to 90%. However, these instances can be terminated at any time if Azure needs the capacity back. This model is perfect for workloads that can tolerate interruptions.
- Hybrid benefit. Companies using Windows Server, SQL Server, or Linux OS can take advantage of the discount program and save up to 76%. You can use the calculator to estimate your savings.
- Savings plan. You can reduce cloud computing costs and save up to 65% on pay-as-you-go services with long-term planning for consistent usage (measured in dollars per hour) over one or three years.
- Dev/test pricing. Organizations can lower costs by up to 57% for a typical web app dev/test environment while developing, testing, and deploying apps. Eligibility requires an existing Visual Studio subscription.
Like AWS, Microsoft Azure offers free trials. Some services, like Azure SQL Database, Azure App Service, Azure Functions, and others, are free up to the specified monthly amounts. Some services are free for the first 12 months. Azure also gives new customers a $200 credit to use in their first 30 days.
Azure pricing models
| Commitment | Upfront costs | Benefit | Limitation | Best for | |
|---|---|---|---|---|---|
| Pay-as-you-go | – | – | On-demand scalability | Expensive in the long run | Variable workloads |
| Reservations | 1 or 3 years | + | Up to 72% less than pay-as-you-go | “Use it or lose it” | Predictable workloads |
| Spot pricing | – | – | Discounted rate of up to 90% off | Termination at any time if Azure needs the capacity back | Workloads that can tolerate interruptions |
| Hybrid benefit | – | – | Up to 76% savings | Windows Server, SQL Server, and Linux core licenses or subscriptions | Migrating existing on-premises workloads to Azure |
| Savings plan | 1 or 3 years | + | Priority use, discount up to 65% | Applies to a specific Azure region and VM type | Predictable workloads |
| Dev/test pricing | – | – | Testing and using environment for development with reduced costs | Existing Visual Studio subscription required,not for production use | Development process |
It is worth noting that as a major competitor of AWS, Azure will provide comparable pricing to AWS for similar services.
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GCP
GCP offers two main options: pay-as-you-go and committed use discounts (CUDs).
The pay-as-you-go model doesn’t require up-front fees or termination charges. You can add and remove services at any time. However, this convenience carries a high hourly cost compared to the other model.
If you require long-term GCP usage and have predictable workloads, CUDs offer greater convenience. Opting for CUD will save you up to 57% on workloads, in exchange for a non-cancellable commitment to a term of one or three years.
Another pricing model—Spot VMs—requires no commitment, offering an economical option for on-demand jobs that leverage excess computing capacity on Google Cloud. However, these instances may be reassigned by the platform as needed. Spot VMs provide variable savings ranging from 60% to 91% compared to on-demand VMs.
GCP also gives new customers a $300 credit to run, test, and deploy solutions in the cloud. It also offers more than 20 products that are always free within monthly usage limits.
GCP’s pricing models
| Pay-as-you-go | CUDs | Spot VMs | |
|---|---|---|---|
| Commitment | – | 1 or 3 years | – |
| Upfront costs | – | + | – |
| Benefit | High flexibility | Cost savings up to 57% | Cost savings up to 91% |
| Limitation | High costs | Non-cancellable obligation | Can be stopped or deleted at any time |
| Best for | Short-term projects and unpredictable workloads | Long-term projects and predictable workloads | Fault-tolerant workloads |
In terms of pricing, the three top cloud providers have a lot in common:
- All three offer a flexible pay-as-you-go model, allowing users to pay for computing capacity by the minute or second without long-term commitments.
- AWS, Azure, and GCP all offer pricing models that allow users to commit to a certain usage for a discounted rate over a one- or three-year term. Each provider offers a form of pricing for using spare capacity at a significantly lower cost.
- AWS, Azure, and GCP all offer free trials and always-free services. Additionally, Azure and GCP provide an initial credit to attract new customers, allowing them to test services without incurring costs.
However, each cloud provider also presents unique options to cater to various user needs:
- AWS offers SP with more flexibility in terms of instance types, regions, and operating systems.
- Azure offers various additional discounts, like its hybrid benefit, that can result in significant savings. Furthermore, Azure’s dev/test pricing represents a cost-effective option for development and testing environments.
- GCP’s CUD model is straightforward: savings for long-term use without the flexibility to change instance types or regions, compared to AWS’s SP.
Cloud pricing models comparison
| AWS | Azure | GCP | |
|---|---|---|---|
| Pay-as-you-go | Yes, billed per second or per hour | Yes, billed per second or minute | Yes, billed per minute |
| Reserved instances | RI, SP | Savings plan | CUDs |
| Discount range for commitments | Up to 75% for RIs | Up to 72% for Reservations | Up to 57% for CUD |
| Cancellation policy for commitment plans | Possible with limitations | Possible for a fee | Not possible |
| Spot instances | Yes | Yes | Yes |
| Free tier | Free trials, 12 months free, always-free services | 12 month free, always-free services | Always-free services |
| Credits | No | $200 for the first 30 days | $300 |
| Unique feature | Flexible saving plans | A range of additional discount programs | Credit without deadline |
Prices for compute instances
For a meaningful comparison, we examined production-ready machines for general purposes with roughly the same features: m5-series (AWS), Dsv5-series (Azure), and N2-series (GCP). All utilize high-performance Intel Xeon processors, offer extensive scalability options, and provide high throughput and low latency, as well as SSD-based temporary storage. However, note that the same vCPUs from different providers can vary in performance.
Concerning the pricing models, our evaluation included pay-as-you-go and savings plans (CUDs for GCP) offered by all three providers. The tables below show the prices for virtual machines per month.
Pay-as-you-go
| AWS | Azure | GCP | |
|---|---|---|---|
| 2 CPU, 8 GB | $70.08 | $70.08 | $70.90 |
| 4 CPU, 16 GB | $140.16 | $140.16 | $141.79 |
| 8 CPU, 32 GB | $280.32 | $280.32 | $283.58 |
| 16 CPU, 64 GB | $560.64 | $560.64 | $567.17 |
The results show that AWS and Azure are competitively priced, while GCP is slightly more expensive. As instances scale up, prices increase proportionally across all providers, with GCP consistently remaining the most expensive, albeit only marginally.
Savings plans (CUDs for GCP) with a one-year commitment
| AWS | Azure | GCP | |
|---|---|---|---|
| 2 CPU, 8 GB | $43.80 | $48.06 | $44.66 |
| 4 CPU, 16 GB | $88.33 | $96.12 | $89.33 |
| 8 CPU, 32 GB | $176.66 | $192.25 | $178.65 |
| 16 CPU, 64 GB | $353.32 | $384.48 | $357.30 |
For savings plans with a one-year commitment across different configurations, AWS generally offers the lowest prices compared to Azure and GCP. GCP’s prices are the next lowest, while Azure has the highest prices in each category.
Savings plans (CUDs for GCP) with a three-year commitment
| AWS | Azure | GCP | |
|---|---|---|---|
| 2 CPU, 8 GB | $29.93 | $32.25 | $31.91 |
| 4 CPU, 16 GB | $60.59 | $64.50 | $63.81 |
| 8 CPU, 32 GB | $121.18 | $129.01 | $127.62 |
| 16 CPU, 64 GB | $242.36 | $258.00 | $255.24 |
Based on the prices provided, Azure tends to be priced in a higher range for all configurations when compared to AWS and GCP. The difference in pricing between the providers is more noticeable as the size of the plan increases. For example, the difference between AWS and Azure at the 16 CPU, 64 GB configuration is $15.64 per month, which would amount to over $560 over the three-year period. Before making the final decision, it is advisable to estimate the project, taking into account the various discount programs offered by Azure, especially if you are using Microsoft’s software packages. To do this, you can use the AWS, Azure, and GCP pricing calculators or entrust this tedious task to an expert team with decades of experience.
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Prices for storage
To compare the storage costs of the three providers, we analyzed the prices of the S3 (AWS), Blob Storage (Azure), and Cloud Storage (GCP) services. The providers offer a variety of tiers tailored to different needs. Here, we focus on standard storage classes suitable for frequently accessed data: S3 Standard (AWS), Hot Access Tier (Azure), and Standard Storage (GCP).
Cloud storage prices vary based on the region and the amount of storage capacity. Therefore, we examined costs across different regions and total storage capacity to highlight not only the price difference but also the dynamics over large volumes.
Cost for 10 TB of storage
| AWS | Azure | GCP | |
|---|---|---|---|
| Northern Virginia | $235.52 / month | $212.99 / month | $214.20 / month |
| Zurich | $275.97 / month | $220.77 / month | $232.83 / month |
| Mumbai | $256.00 / month | $204.80 / month | $186.26 / month |
For instance, for 10 TB of storage, GCP is the most cost-effective option in Mumbai, while Azure is slightly cheaper in Zurich and Northern Virginia. Conversely, AWS is the most expensive in all three regions for this storage amount.
Cost for 100 TB of storage
| AWS | Azure | GCP | |
|---|---|---|---|
| Northern Virginia | $2,304.00 / month | $2,087.32 / month | $2,142.04 / month |
| Zurich | $2,703.36 / month | $2,165.45 / month | $2,328.31 / month |
| Mumbai | $2,508.80 / month | $2,007.04 / month | $1,862.65 / month |
As we extend our analysis to 100 TB of storage, AWS continues to have the highest prices. In contrast, Azure offers more competitive rates in Northern Virginia and Zurich, undercutting GCP.
Cost for 500 TB of storage
| AWS | Azure | GCP | |
|---|---|---|---|
| Northern Virginia | $11,315.20 / month | $10,266.21 / month | $10,710.21 / month |
| Zurich | $13,291.52 / month | $10,658.10 / month | $11,641.53 / month |
| Mumbai | $12,339.20 / month | $9,871.36 / month | $9,313.23 / month |
In summary, for these specified storage amounts and regions, GCP and Azure are competitive with each other, while AWS consistently charges higher prices. Importantly, across all providers and regions, as the storage size increases, the cost per TB tends to decrease, meaning that you pay less by using more.
For businesses evaluating cloud storage options, these cost differences play a vital role in selecting the best cloud storage provider in a region or determining the most cost-efficient data location, assuming compliance and technical requirements are met.
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Explore our expertiseConclusion
Declaring a definitive leader in cloud provider cost-effectiveness is challenging, as the cost of specific services varies by provider. Selecting the right cloud provider requires a thorough examination of their pricing models, potential discounts, and specific features that align with the organization’s infrastructure, strategic goals, and a particular solution. Utilizing specialized pricing calculators facilitates this decision-making process.
If you want to navigate this vast sea of information without wasting time and becoming overwhelmed, consider consulting with the seasoned experts at EffectiveSoft. We will assess your needs, capabilities, and existing infrastructure and guide you toward the perfect cloud solution for your organization.
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