Azure Cosmos DB Pricing
This document provides a comprehensive overview of the pricing model for Azure Cosmos DB, a globally distributed, multi-model database service. Understanding these costs is crucial for optimizing your application's performance and budget.
Key Pricing Components
Azure Cosmos DB pricing is primarily based on two main components:
- Request Units (RUs): The throughput provisioned for your database operations.
- Storage: The amount of data stored in your Cosmos DB containers.
Request Units (RUs)
Request Units are a normalized measure of the compute, memory, and I/O resources required to perform database operations. The number of RUs consumed by an operation depends on factors such as:
- Operation type (read, write, query, delete)
- Number of items read or written
- Size of items
- Consistency level
- Presence and complexity of queries
You can provision RUs in two ways:
- Manual Throughput: You specify a fixed number of RUs per second (RU/s) for a container or database.
- Autoscale Throughput: Azure Cosmos DB automatically scales your throughput from a minimum to a maximum RU/s based on your workload, ensuring you only pay for what you need.
Storage
Storage costs are based on the total gigabytes (GB) of data stored in your Cosmos DB containers. This includes:
- The actual data stored.
- Indexes associated with your data.
- Transactional backfill storage.
Note that storage is billed per GB-month. For example, if you store 10 GB for half a month, you'll be charged for 5 GB-months.
Pricing Tiers and Options
Azure Cosmos DB offers different pricing models and tiers:
1. Standard Pricing (Provisioned Throughput]
This is the most common model where you provision RU/s and storage. Pricing varies by:
- Region: Costs differ based on the Azure region where your Cosmos DB account is deployed.
- API: While the core concept of RUs is consistent, pricing might have slight variations based on the API used (SQL, MongoDB, Cassandra, Gremlin, Table).
2. Serverless Pricing
For workloads with infrequent or unpredictable traffic, the serverless option can be cost-effective. You pay per operation (based on RUs consumed) and for storage, without needing to provision throughput upfront. Ideal for development/testing or applications with spiky traffic patterns.
3. Azure Cosmos DB Dedicated Clusters
For mission-critical, high-throughput workloads, dedicated clusters offer predictable performance and pricing. This option is typically for enterprise-level scenarios.
Example Pricing Calculation (Illustrative)
Let's consider a simplified example for manual throughput in the East US region (prices are illustrative and subject to change):
| Component | Unit | Estimated Cost (USD) |
|---|---|---|
| Provisioned Throughput (RU/s) | Per million RU/s per month | $0.018 |
| Storage | Per GB per month | $0.18 |
Scenario: You provision 10,000 RU/s and store 50 GB of data for a full month in East US.
- Throughput Cost: (10,000 RU/s / 1,000,000) * $0.018 * 730 hours/month ≈ $1.80
- Storage Cost: 50 GB * $0.18/GB ≈ $9.00
- Total Estimated Cost: $1.80 + $9.00 = $10.80
This is a simplified calculation. Actual costs can vary. Always refer to the official Azure pricing calculator for precise estimates.
Cost Optimization Strategies
- Choose the Right Throughput Mode: Select manual for predictable workloads and autoscale for variable ones. Consider serverless for low-traffic or unpredictable scenarios.
- Optimize Queries: Efficient queries consume fewer RUs. Use indexing effectively and avoid cross-partition queries when possible.
- Monitor RU Consumption: Regularly monitor your RU usage to identify potential bottlenecks or over-provisioning.
- Data Lifecycle Management: Implement policies to delete or archive old data to reduce storage costs.
- Leverage Azure Hybrid Benefit: If you have existing SQL Server licenses, you might be eligible for cost savings.
Free Tier and Trial
Azure Cosmos DB offers a Free Tier that includes a limited amount of free throughput and storage per account. Additionally, new Azure customers can take advantage of a free Azure trial.