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Important
Azure Cosmos DB for PostgreSQL is on a retirement path and no longer recommended for new projects. Instead, use one of these two services:
For PostgreSQL workloads, use the Elastic Clusters feature of Azure Database For PostgreSQL to take advantage of horizontal scale-out and distributed PostgreSQL features within the open source Citus extension. For migration guidance, see migrate to Azure Database for PostgreSQL with Elastic Cluster.
For NoSQL workloads, use Azure Cosmos DB for NoSQL for a distributed database solution that includes a 99.999% availability service level agreement (SLA), instant autoscale, and automatic failover across multiple regions.
For existing Azure Cosmos DB for PostgreSQL deployments only, building scalable apps involves three steps. New projects must use one of the alternative services listed earlier and shouldn't follow the steps in this article.
- Classify your application workload. Common workloads where Azure Cosmos DB for PostgreSQL shines include:
- Multitenant SaaS → tenant-isolated schemas or shard keys
- Microservices → service-aligned distributed tables
- Real-time operational analytics → co-located distributed data
- High-throughput OLTP → row-based sharding with a high-cardinality key
- Based on the workload, use schema-based sharding or identify the optimal shard key for the distributed
tables (for example, shard by
tenant_idfor a multitenant SaaS app so that all rows for a tenant are co-located; expected result: queries scoped to a tenant are routed to a single shard). Classify your tables as reference, distributed, or local. - When using row-based sharding, update the database schema and application queries to optimize performance across nodes.
Success check: After completing these steps, tenant- or shard-key–scoped queries consistently target a single worker node and show stable low latency under load.
Next steps
Before you build a new app, review the architecture of Azure Cosmos DB for PostgreSQL.