Introduction

After engaging in conversations with hundreds of CTOs across diverse industries, geographies, and company sizes, one recurring theme became clear: AWS pricing is complex and often misunderstood. Despite being a foundational element of cloud strategy, regional pricing remains opaque, often clouded by misconceptions or oversimplified assumptions.

In reality, AWS pricing is highly variable across regions and shaped by a complex interplay of structural, economic, and strategic factors:

• Infrastructure Cost Variance: Local differences in electricity, real estate, labor, and cooling costs are reflected in regional AWS pricing models. These fundamental inputs drive meaningful cost disparities.
• Economies of Scale: High-demand regions, particularly in the US benefit from scale efficiencies, enabling AWS to offer lower prices. Conversely, smaller or emerging regions typically bear higher costs due to reduced operational leverage.
• Regulatory Compliance: Markets with stringent data residency or compliance laws often see elevated AWS pricing, driven by increased operational overhead for maintaining local infrastructure and adhering to legal requirements.
• Infrastructure density: Regions like São Paulo or Cape Town may command a premium due to lower infrastructure density or regional demand constraints.
• Strategic Price Positioning: AWS may choose to subsidize certain regions to accelerate adoption or establish early market dominance, while pricing more mature regions based on competitive dynamics and operational maturity.

Cloud cost is deeply tied to geography. For FinOps professionals, cloud architects, and CTOs, a nuanced understanding of these regional pricing patterns is essential for balancing cost, performance, compliance, and risk.

This report aims to offer a data-backed foundation for evaluating regional cloud pricing with greater precision. While we recognize that pricing is only one aspect of regional decision-making factors like latency, data sovereignty, and service availability are equally critical. Our objective is to contribute meaningful clarity to an often complex calculus.

We hope this white paper helps inform smarter workload placement decisions and supports the broader mission of building cost-aware, resilient cloud architectures.

1. Methodology

To assess price disparities across AWS regions, we built a normalized price index, which enables a like-for-like comparison across regions.

Data sources

Individual SKU correspond to unique combinations of service name, region code, usage type and operation.

Only the first paid tier was taken into account for each SKU, thereby excluding any free tier pricing.

The analysis focuses exclusively on baseline On-Demand prices, with discounts from Savings Plans, Reserved Instances, and Private Pricing Agreements being intentionally excluded. This methodology ensures a standardized view of pricing differentials, supporting more objective cloud cost governance and optimized workload placement decisions.

The pricing data that supports the analyses in this white paper originates from the AWS Price List Bulk API, which provides prices for all AWS services across all regions.

Index construction

For regional price comparisons, all prices were indexed against us-east-1 (Northern Virginia), chosen as our reference point (index = 100). This region was selected due to:

• Its status as AWS’s oldest and most mature region,
• Its high availability and competitive pricing environment,
• Its role as the de facto reference point in AWS pricing documentation.

To support broader comparisons, we also computed geographic area-level indices by grouping data by region prefix (e.g., eu-, ap-, sa-), mainly corresponding to areas (e.g., eu = Europe). These area indices were aggregated from underlying SKU-level data.

2. Executive Summary

Overall Pricing Insights

Our analysis of 12 core AWS services reveals meaningful price variations across regions and countries, with disparities ranging from modest to extreme. Services like EC2 and Lambda exhibit relatively stable global pricing, whereas SageMaker, ElastiCache, and Redshift show highly volatile patterns. These findings underscore the importance of strategic workload placement and pricing awareness in multi-region AWS environments.

Most Competitive and Most Expensive Areas

Across all services, the United States consistently remains the cheapest region, while South America displays the highest overall uplift, averaging +54.8 percentage points vs. the US region.

Most Competitive and Most Expensive Countries

Among the countries analyzed, India emerges as the cheapest location, particularly for EC2 services, with a price index as low as 93%. On the other end of the spectrum, Hong Kong registers the highest price point, with SageMaker costs peaking at 281% of the U.S. baseline. This extreme gap illustrates how regional pricing discrepancies can significantly impact overall cloud infrastructure budgets.

EC2 and RDS Pricing Insights

Both EC2 and RDS serve as foundational building blocks in most AWS-based architectures.

• EC2 pricing demonstrates low to moderate variation across regions. With a standard deviation of 7% and an average absolute deviation also at 7%, the service maintains a high degree of cost predictability globally. When comparing EC2 pricing geographically, India offers the lowest index at 93%, while Brazil is the most expensive at 131%. This 38 percentage point difference, though moderate relative to other services, remains material for large-scale compute deployments.

• RDS exhibits medium to high variation in pricing across countries. A standard deviation of 13% and an average absolute deviation of 19% indicate that organizations leveraging this managed database service should pay close attention to geographic pricing when designing multi-region architectures. RDS pricing remains the cheapest in the US but climbs as high as 164% in Brazil. This 64% uplift can significantly impact database-heavy workloads if not proactively optimized.

What’s Next

In the following sections, we provide a detailed pricing breakdown for each of the 12 AWS services analyzed. For every service, we outline key cost insights, highlight regional outliers, and quantify pricing volatility using standardized KPIs

3. Service-Level

3.1.  Elastic Compute Cloud (EC2)

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Amazon EC2 (Elastic Compute Cloud) is the foundational compute service of AWS, allowing organizations to run virtual machines at scale with granular control over performance, capacity, and cost. As a core building block for modern cloud architectures, EC2 powers everything from development environments to latency-sensitive applications and large-scale distributed systems.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals medium country-level price disparities. The global average price index is 112%, with a minimum of 93% (India) and a maximum of 131% (Brazil). The standard deviation of 7% highlights moderate volatility, while a median of 107% suggests that more than half of country prices are above the US benchmark. The average absolute deviation (7%) confirms a consistent global uplift in compute costs relative to the baseline.

3.2.  Elastic Container Service (ECS)

Amazon Elastic Container Service (ECS) is AWS’s fully managed container orchestration service, enabling users to run and scale containerized applications without managing the underlying infrastructure. It supports both EC2 and Fargate launch types, offering flexibility in performance, cost, and operational control for microservices architectures and batch workloads.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals moderate country-level price disparities. The global average price index is 124%, with a minimum of 98% and a maximum of 158%. The standard deviation of 12% indicates medium volatility, while a median of 113% suggests that more than half of country prices are above the U.S. benchmark. The average absolute deviation (15%) confirms a consistent uplift in ECS pricing across global regions relative to the baseline.

3.3.  Lambda

AWS Lambda is a serverless compute service that lets developers run code without provisioning or managing servers. It automatically scales applications by running code in response to events and charging only for the compute time consumed, making it a cost-effective solution for event-driven architectures.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals moderate country-level price disparities. The global average price index is 116%, with a minimum of 100% and a maximum of 133%. The standard deviation of 10% highlights limited volatility, while a median of 108% indicates that more than half of country prices are above the U.S. benchmark. The average absolute deviation (11%) confirms a globally consistent uplift in Lambda pricing relative to the baseline.

3.4.  SageMaker (SGM)

Amazon SageMaker is AWS’s flagship service for building, training, and deploying machine learning models at scale. It abstracts much of the underlying infrastructure complexity while offering a broad set of ML tools from model training to real-time inference within a fully managed environment. Given its intensive compute and storage usage, SageMaker pricing is particularly sensitive to regional infrastructure costs.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals significant country-level price disparities. The global average price index is 145%, with a minimum of 99% and a maximum of 281% (Hong Kong). The standard deviation of 33% highlights strong volatility, while a median of 118% indicates that more than half of country prices are well above the US benchmark. The average absolute deviation (24%) confirms a pronounced global uplift in SageMaker costs relative to the baseline.

3.5.  Simple Storage Service (S3)

Amazon S3 is AWS’s object storage service, designed for scalability, durability, and low-latency access. It is widely used for data lakes, backups, static website hosting, and application data storage, offering a tiered pricing model based on access frequency and storage class.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals moderate country-level price disparities. The global average price index is 119%, with a minimum of 100% and a maximum of 144%. The standard deviation of 8% indicates limited volatility, while a median of 110% suggests that the majority of country prices are above the U.S. benchmark. The average absolute deviation (10%) confirms a relatively consistent global uplift in object storage costs relative to the baseline.

3.6.  Relational Database Service (RDS)

Amazon RDS is AWS’s managed relational database service, supporting engines such as MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server. It abstracts away operational overhead by automating tasks like provisioning, backups, patching, and scaling, allowing teams to focus on application development and performance optimization.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals significant country-level price disparities. The global average price index is 131%, with a minimum of 100% and a maximum of 164%. The standard deviation of 13% reflects strong pricing volatility, while a median of 117% suggests that more than half of country prices are notably above the U.S. benchmark. The average absolute deviation (19%) confirms a consistent global uplift in RDS pricing relative to the baseline.

3.7.  ElastiCache

Amazon ElastiCache is a fully managed in-memory caching service supporting Redis and Memcached. It is designed to optimize application performance by reducing latency and offloading demand from primary databases, making it ideal for real-time analytics, session stores, and caching layers in distributed systems.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals significant country-level price disparities. The global average price index is 131%, with a minimum of 100% and a maximum of 175%. The standard deviation of 16% highlights noticeable volatility, while a median of 119% indicates that more than half of countries price well above the U.S. benchmark. The average absolute deviation (22%) confirms a substantial global uplift in ElastiCache pricing relative to the baseline.

3.8.  Open Search (AOS)

Amazon OpenSearch Service is AWS’s managed search and analytics engine, used to ingest, index, and visualize large volumes of log and event data in real-time. It supports open-source Elasticsearch APIs and integrates natively with AWS services, making it a key component for observability, security analytics, and full-text search use cases.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals considerable country-level price disparities. The global average price index is 127%, with a minimum of 91% and a maximum of 164%. The standard deviation of 14% highlights moderate volatility, while a median of 118% suggests that more than half of country prices are significantly above the U.S. benchmark. The average absolute deviation (17%) confirms a notable global uplift in OpenSearch pricing relative to the baseline.

3.9.  Dynamo DB (DDB)

Amazon DynamoDB is AWS’s fully managed NoSQL database service, designed for high performance applications requiring millisecond latency at any scale. It supports both document and key-value store models and is often used in serverless architectures, real-time analytics, and mobile backends.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals notable country-level price disparities. The global average price index is 124%, with a minimum of 97% and a maximum of 162%. The standard deviation of 14% highlights substantial volatility, while a median of 110% indicates that more than half of country prices are above the US benchmark. The average absolute deviation (15%) confirms a meaningful global uplift in DynamoDB costs relative to the baseline.

3.10.  Redshift

Amazon Redshift is AWS’s fully managed cloud data warehouse service, designed for large-scale analytics workloads. It enables organizations to run complex queries across vast datasets using standard SQL and integrates seamlessly with the broader AWS ecosystem, offering high performance and scalability for modern data pipelines.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals significant country-level price disparities. The global average price index is 129%, with a minimum of 98% and a maximum of 208%. The standard deviation of 26% highlights strong pricing volatility, while a median of 114% suggests that more than half of country prices are well above the U.S. benchmark. The average absolute deviation (23%) confirms a pronounced global uplift in Redshift costs relative to the baseline.

3.11.  Cloud Front (CF)

Amazon CloudFront is AWS’s content delivery network (CDN) service, designed to deliver data, videos, applications, and APIs to users globally with low latency and high transfer speeds, leveraging a network of edge locations.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals moderate country-level price disparities. The global average price index is 116%, with a minimum of 100% and a maximum of 138%. The standard deviation of 9% highlights moderate volatility, while a median of 107% indicates that more than half of country prices are above the US benchmark. The average absolute deviation (7%) confirms a consistent global uplift in CloudFront costs relative to the baseline.

3.12.  Elastic Load Balancing (ELB)

Elastic Load Balancing (ELB) automatically distributes incoming application traffic across multiple targets such as Amazon EC2 instances, containers, and IP addresses in one or more Availability Areas. It ensures high availability, scalability, and fault tolerance for applications running on AWS.

Using US East (N. Virginia) as the baseline (index 100), our analysis reveals moderate country-level price disparities. The global average price index is 110%, with a minimum of 94% and a maximum of 133%. The standard deviation of 10% highlights modest volatility, while a median of 103% indicates that just over half of country prices are slightly above the U.S. benchmark. The average absolute deviation (5%) confirms a relatively tight global price alignment for ELB services relative to the baseline.

Conclusion

To assess price disparities across AWS regions, we built a normalized price index, which enables a like-for-like comparison across regions.

Optimizing cloud costs is no longer just a matter of instance types or reserved capacity, it’s about thinking globally. By understanding how AWS regional pricing works and how to leverage regional differences strategically, you can unlock significant savings without compromising on performance or reliability.

From evaluating cost disparities between regions to designing a multi-region architecture, every decision has the potential to impact your bottom line. We encourage you to continue exploring these opportunities and take control of your cloud budget with clarity and confidence.

We hope this comprehensive guide has equipped you with the knowledge and tools you need to make smarter, more cost-effective decisions on AWS.

At Opsima, we are specialized in a very targeted area of FinOps: managing financial commitments (Savings Plans / Reserved Instances) in an autonomous and intelligent way to reduce your cloud bill.  

If you have any questions, feel free to reach out to us at contact@opsima.ai.

We’ll be happy to help!

Thank you for reading,

The Opsima Team

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