Classify application workload in Azure Cosmos DB for PostgreSQL

APPLIES TO: Azure Cosmos DB for PostgreSQL (powered by the Citus database extension to PostgreSQL)

Here are common characteristics of the workloads that are the best fit for Azure Cosmos DB for PostgreSQL.

Prerequisites

This article assumes you know the fundamental concepts for scaling. If you haven't read about them, take a moment to do so.

Tenants see their own data; they can't see other tenants' data.
Most B2B SaaS apps are multi-tenant. Examples include Salesforce or Shopify.
In most B2B SaaS apps, there are hundreds to tens of thousands of tenants, and more tenants keep joining.
Multi-tenant SaaS apps are primarily operational/transactional, with single digit millisecond latency requirements for their database queries.
These apps have a classic relational data model, and are built using ORMs – like RoR, Hibernate, Django etc.

These apps have a customer/user facing interactive analytics dashboard, with a subsecond query latency requirement.
High concurrency required - at least 20 users.
Analyzes data that's fresh, within the last one second to few minutes.
Most have time series data such as events, logs, etc.
Common data models in these apps include:
- Star Schema - few large/fact tables, the rest being small/dimension tables
- Mostly fewer than 20 major tables

Run NoSQL/document style workloads, but require PostgreSQL features such as transactions, foreign/primary keys, triggers, extension like PostGIS, etc.
The workload is based on a single key. It has CRUD and lookups based on that key.
These apps have high throughput requirements: thousands to hundreds of thousands of TPS.
Query latency in single-digit milliseconds, with a high concurrency requirement.
Time series data, such as internet of things.

Choose whichever fits your application the best: