Azure vs AWS vs Google Cloud Storage Calculator
Estimate monthly object storage cost across Microsoft Azure Blob Storage, Amazon S3, and Google Cloud Storage using storage volume, egress, operations, region, and redundancy. This calculator uses representative public list pricing assumptions for common tiers and gives you a fast side by side comparison.
Estimator assumptions: pricing varies by region, API type, minimum retention rules, free tiers, and negotiated enterprise discounts. Treat this as a planning calculator and validate final numbers with each provider’s current pricing page.
Estimated monthly results
Enter your workload and click Calculate cloud storage costs to compare providers.
Expert guide to using an Azure vs AWS vs Google Cloud Storage calculator
An Azure vs AWS vs Google Cloud Storage calculator is useful because raw storage price is only one part of the monthly bill. Teams often compare the listed price per GB and stop there, but real object storage cost is influenced by at least five major variables: how much data is stored, where it is stored, which storage tier is chosen, how often data is downloaded, and how many operations are performed. Once you add redundancy choices such as local, zone, or geo replication, costs can diverge materially between Microsoft Azure Blob Storage, Amazon S3, and Google Cloud Storage.
This calculator is designed to make that comparison easier. It models monthly cost with representative public list rates for common storage tiers and regions, then adds internet egress and request charges. The result is a cleaner apples to apples view for planning. If you are budgeting a migration, designing a media archive, storing backups, or estimating unit economics for a SaaS product, a side by side calculator helps you quickly identify which provider is cheapest for a specific pattern rather than in the abstract.
It is also important to understand that cloud object storage is not a single product. AWS has S3 Standard, S3 Standard-IA, Glacier classes and many related options. Azure Blob Storage offers Hot, Cool, and Archive with different replication models like LRS and GRS. Google Cloud Storage provides Standard, Nearline, Coldline, and Archive, plus regional and multi regional placement choices. A realistic storage calculator therefore needs to reflect both capacity and behavior. A workload with high downloads can be much more expensive than a write once, read rarely archive even if total stored data is identical.
What the calculator estimates
- Storage cost: The monthly cost of storing your data volume in the selected storage class and region profile.
- Egress cost: Approximate charges for sending data out to the public internet.
- Request cost: Read and write API operation cost based on the count you provide.
- Redundancy premium: A multiplier to simulate single region versus geo redundant or multi region storage.
- Total estimated monthly cost: The combined amount used for the side by side provider comparison and chart.
Representative pricing assumptions used in this calculator
The numbers below are simplified but grounded in widely cited public list pricing patterns for common US region object storage tiers. Because vendor pricing changes, differs by exact region, and can include minimum retention and retrieval nuances, always verify before procurement. The goal here is comparison speed, not invoice level precision.
| Tier mapping | AWS reference | Azure reference | Google Cloud reference | Representative US storage rate |
|---|---|---|---|---|
| Standard / Hot | S3 Standard | Blob Hot (LRS baseline) | Cloud Storage Standard Regional | AWS $0.023/GB, Azure $0.0184/GB, Google $0.020/GB |
| Infrequent | S3 Standard-IA | Blob Cool | Nearline | AWS $0.0125/GB, Azure $0.010/GB, Google $0.010/GB |
| Archive | S3 Glacier Flexible Retrieval | Blob Archive | Coldline | AWS $0.004/GB, Azure $0.00099/GB, Google $0.004/GB |
Those baseline storage rates are only the beginning. Egress and operations can substantially influence the result. For many application workloads, internet egress is the largest variable after storage itself. That is why the calculator asks for monthly outbound data separately. It also asks for read and write requests because object storage APIs are metered, usually at different rates for PUT class and GET class operations.
Why real world storage bills differ from sticker price
People often search for the cheapest cloud storage provider and expect a universal answer. In practice, there is no single winner for every workload. Azure may look attractive for hot storage in one geography, AWS may be competitive in standard tiers for ecosystems built around S3 tooling, and Google Cloud may be compelling when a workload aligns with its regional and dual region storage architecture. The right answer depends on your traffic pattern.
- Storage footprint: More stored data scales linearly with per GB price, making tier selection critical.
- Access frequency: Hot tiers cost more to store but are friendlier for frequent reads. Cold tiers are cheaper to store but often add access or retrieval penalties and minimum retention rules.
- Data transfer: If users download large amounts of data, egress can dominate total monthly spend.
- Replication and resilience: Geo redundant or multi regional storage improves resilience but costs more.
- Request intensity: Billions of small object operations can add up in content platforms, data pipelines, and backup systems.
Service durability and availability statistics matter too
Price is not the only selection criterion. Durability, availability targets, compliance, ecosystem fit, and data management features all influence provider choice. Public vendor documentation commonly cites very high durability for object storage systems, often expressed as eleven nines for annual durability in flagship classes. Availability commitments differ by redundancy option and region architecture, so your storage calculator should be interpreted alongside service level goals.
| Provider | Well known object storage platform | Public durability figure often cited | Typical high availability target in premium redundant configurations | Planning implication |
|---|---|---|---|---|
| AWS | Amazon S3 | 99.999999999% durability for designed object durability in common documentation | Varies by class and architecture, often up to 99.99% for selected configurations | Strong ecosystem and broad integration make S3 a common baseline in calculators. |
| Azure | Azure Blob Storage | Designed for very high durability with replicated copies across selected redundancy options | Often up to 99.99% for read access geo or zone based designs depending on SKU | Replication choice can materially alter cost, so compare LRS versus GRS carefully. |
| Google Cloud | Google Cloud Storage | 11 nines durability is commonly cited for several storage offerings | Regional and dual region choices can deliver strong availability targets | Dual region and multi region patterns can improve resilience with a premium over single region storage. |
How to interpret the results from this calculator
If the calculator shows only a small monthly spread between providers, do not over optimize on pennies per GB. In those situations, non price factors may matter more. Examples include lifecycle policy maturity, event integrations, CDN alignment, data lake tooling, identity and access management consistency, and backup or archive workflows. On the other hand, if one provider appears dramatically cheaper, investigate which component created the difference. It may be lower base storage, lower egress assumptions, or a redundancy model that is not exactly equivalent across clouds.
A practical way to use the results is to break your workload into scenarios:
- Active application storage: Standard or hot class, moderate requests, meaningful egress.
- Backup repository: Infrequent tier, low read volume, occasional restore spikes.
- Long term archive: Archive tier, very low requests, low routine egress, but possible retrieval costs in event driven access.
- Global distribution: Geo or multi region storage, often paired with CDN and replication strategy analysis.
When Azure tends to look strong
Azure Blob Storage frequently attracts organizations that already run Microsoft centric estates. Identity integration through Microsoft Entra, governance alignment with Azure Policy, and operational familiarity can reduce total platform friction. In many pricing snapshots, Azure Hot Blob storage has been competitive on base storage cost in common US regions. That does not automatically make Azure the cheapest all in option, but it means Azure often performs well in calculators when workloads store substantial data and do not have extreme egress or retrieval patterns.
When AWS tends to look strong
AWS remains the default point of comparison for many infrastructure teams because Amazon S3 has broad ecosystem support, mature lifecycle controls, extensive event integrations, and near universal compatibility in tooling. If your engineering platform already uses S3 heavily, operational efficiency may outweigh a slightly higher or lower list price. AWS also offers a large menu of adjacent services, so architecture convenience can reduce indirect cost even if direct storage cost is not the absolute minimum in every scenario.
When Google Cloud tends to look strong
Google Cloud Storage can compare favorably in data analytics centric environments, especially where organizations want strong integration with BigQuery, data processing pipelines, or Google distributed network design. Google storage classes are relatively straightforward, and for some workloads the balance of regional pricing and operations can be appealing. As with any provider, the right answer depends on your access pattern rather than the marketing headline.
Important limitations every buyer should remember
- Archive and cold classes may have minimum storage duration rules. Deleting early can create extra charges.
- Retrieval pricing can apply to colder classes and is not fully modeled in this simplified calculator.
- Enterprise agreements, committed spend, and partner discounts can materially change rankings.
- Inter region transfer, replication traffic, and private connectivity are separate considerations.
- Object count, metadata patterns, and versioning can alter your bill beyond simple GB estimates.
Best practices for choosing between Azure, AWS, and Google Cloud for storage
- Model at least three scenarios. Compare current usage, expected 12 month growth, and a peak recovery month.
- Separate hot data from cold data. Many teams overpay by placing all objects in a premium tier.
- Estimate egress honestly. Downloads, restores, and public serving patterns often surprise finance teams.
- Check data residency and compliance needs. Region design can limit which pricing model is acceptable.
- Use lifecycle policies. Automated tier transitions usually improve long term economics.
- Test invoice mechanics. Run a proof of concept and compare real bill exports before full migration.
Authoritative resources for further research
For architecture, security, and cloud cost governance context, the following public resources are useful:
- NIST: The NIST Definition of Cloud Computing
- CISA: Cloud Security Technical Reference Architecture
- University of California, Berkeley resources and publications are widely referenced in cloud computing research and strategy discussions.
Bottom line
An Azure vs AWS vs Google Cloud Storage calculator is most valuable when it goes beyond headline storage price and includes traffic, operations, and resilience choices. That is exactly why this tool asks for storage volume, monthly egress, request counts, storage class, region, and redundancy. Use it to narrow your short list fast, then validate the assumptions against the latest provider pricing pages and your real telemetry. In most buying decisions, the best provider is not the one with the lowest theoretical price. It is the one with the lowest realistic total cost for your workload while still meeting resilience, performance, and governance requirements.