Azure Cosmos DB Pricing

Pricing Models

Azure Cosmos DB offers flexible pricing models to suit your needs, including throughput (Request Units per second - RU/s) and storage.

Throughput Pricing (RU/s)

Request Units (RUs) are a normalized measure of throughput. The cost is based on the number of RUs provisioned per second and the duration for which they are provisioned.

Region	API	Provisioned Throughput (RU/s)	Estimated Cost per RU/s per Month (USD)	Notes
West US 2	Core (SQL)	100 RU/s	$0.010 - $0.018	Standard consistency
West US 2	Core (SQL)	100 RU/s	$0.012 - $0.022	Strong consistency
East US	MongoDB	1000 RU/s	$0.015 - $0.025	Varies by consistency level
North Europe	Cassandra	500 RU/s	$0.008 - $0.015	Throughput cost
Japan East	Table	200 RU/s	$0.009 - $0.017	Standard tier

Storage Pricing

Storage is billed based on the amount of data stored in GB per month. Different regions and consistency models may have slight variations.

Region	Storage (GB per Month)	Estimated Cost (USD)	Notes
Global	First 50 GB	$0.18 - $0.25	Includes data and index
Global	Additional GB	$0.01 - $0.03	After initial 50 GB

Autoscale Pricing

Autoscale automatically scales your throughput based on demand, ensuring you only pay for what you use while maintaining performance. It's typically priced at a multiplier of the provisioned throughput tier.

100 RU/s Autoscale (scales up to 1000 RU/s): Approx. $0.07 - $0.12 per hour
1000 RU/s Autoscale (scales up to 10,000 RU/s): Approx. $0.70 - $1.20 per hour

Key Pricing Factors

Provisioned Throughput (RU/s): The core determinant of cost for read and write operations.
Storage: Cost of storing your data (documents, indexes).
API Choice: Different APIs (SQL, MongoDB, Cassandra, Gremlin, Table) may have slightly different RU/s cost profiles.
Consistency Level: Stronger consistency levels can incur higher RU/s costs.
Region: Costs can vary slightly by Azure region.
Data Transfer: Standard Azure data transfer charges apply for data moving in and out of Azure regions.

Cost Optimization Tips

Leverage Autoscale: Ideal for workloads with variable traffic patterns.
Right-size your RU/s: Monitor usage and adjust provisioned throughput accordingly.
Optimize Queries: Efficient queries consume fewer RUs.
Choose the right Consistency Level: Select the lowest acceptable consistency for your application to save costs.
Use partitioned containers effectively: Proper partitioning can improve performance and cost-efficiency.

Start Building with Azure Cosmos DB

Explore the pricing calculator for detailed estimates and understand the cost implications for your specific scenario.

Go to Pricing Calculator