Understanding Azure Cosmos DB Pricing

Azure Cosmos DB is a globally distributed, multi-model database service that enables you to harness the benefits of horizontal scaling and global distribution. Its pricing is primarily based on throughput (Request Units per second - RU/s) and storage consumed. Understanding these components is key to optimizing your costs.

Key Pricing Components

  • Throughput (Request Units - RU/s): This is the most significant factor. You provision a certain number of RUs per second, which dictates the database's capacity to handle operations. Higher throughput means higher costs.
  • Storage: The amount of data you store in your database contributes to the cost.
  • Backup & Restore: Features like automatic backups and long-term retention incur additional charges.
  • Inter-Region Writes: If you configure multi-region writes, there's a cost associated with the additional write throughput provisioned in secondary regions.
  • Networking: Data egress to regions outside of Azure or over public endpoints can incur networking charges.

Throughput Provisioning Models

Azure Cosmos DB offers two primary throughput provisioning models:

Autoscale ~$0.050 / 1000 RU/s / hour

Scales automatically up to a maximum RU/s based on usage. Ideal for unpredictable workloads.

Manual ~$0.040 / 1000 RU/s / hour

You set a fixed RU/s. Best for predictable, consistent workloads.

Storage Pricing

Storage is charged based on the normalized size of your data and indexes. The rate is typically around:

Normalized Storage ~$0.180 / GB / month

This includes data, indexes, and transaction logs.

Pricing Considerations

The specific cost for your Azure Cosmos DB deployment will depend on several factors:

  • Region(s): Pricing varies slightly by Azure region.
  • API: While the core RU/s and storage pricing is similar, some specific features or offerings might have slight variations across APIs (Core SQL, MongoDB, Cassandra, Gremlin, Table).
  • Consistency Level: Higher consistency levels can sometimes have a slightly higher RU cost for reads.
  • Indexing Policy: An optimized indexing policy can reduce storage and improve performance, indirectly affecting cost.

Cost Optimization Tips

  • Right-size your RU/s: Monitor your consumption and adjust provisioned throughput accordingly. Use autoscale for variable workloads.
  • Optimize Storage: Remove unused data, implement TTL (Time-to-Live) policies, and ensure your indexing policy is efficient.
  • Choose the right region: Deploy your database in the Azure region closest to your users to minimize latency and potential networking costs.
  • Leverage Azure Hybrid Benefit: If you have existing SQL Server licenses, you may be eligible for cost savings.

Ready to estimate your costs?

Use the Azure Pricing Calculator for a detailed breakdown.