Azure SQL Database and Azure Cosmos DB
Azure SQL Database and Azure Cosmos DB—two powerful but fundamentally different offerings from Microsoft Azure—are compared here in terms of architecture, use cases, and best practices.
🧩 What Is Azure SQL Database?
Azure SQL Database is a fully managed relational database-as-a-service (DBaaS) built on SQL Server. It’s ideal for structured data and traditional transactional workloads.
🔹 Key Features
- Relational model with ACID compliance
- T-SQL support and compatibility with SQL Server tools
- Built-in high availability, backups, and disaster recovery
- Elastic pools for cost-efficient multi-tenant hosting
- Security & compliance: encryption, auditing, threat detection
✅ Best Use Cases
- Line-of-business apps (ERP, CRM)
- Structured data with complex joins
- Reporting and analytics with SQL
- Legacy apps migrating from on-prem SQL Server
🌍 What Is Azure Cosmos DB?
Azure Cosmos DB is a globally distributed, multi-model NoSQL database designed for high scalability and low latency.
🔹 Key Features
- Multi-model support: document (JSON), key-value, graph, column-family
- APIs: SQL (for JSON), MongoDB, Cassandra, Gremlin, Table
- Global distribution with multi-region writes
- Five consistency levels: strong to eventual
- Auto-scaling throughput via Request Units (RUs)
✅ Best Use Cases
- Real-time apps with massive scale (IoT, gaming, social)
- Unstructured or semi-structured data
- Multi-region apps needing low latency
- Schema-less design for agile development
⚖️ Azure SQL vs Azure Cosmos DB: Comparison Table
| Feature |
Azure SQL Database |
Azure Cosmos DB |
| Data Model |
Relational (tables, rows, columns) |
NoSQL (documents, key-value, graph, etc.) |
| Schema |
Fixed schema |
Schema-less |
| Query Language |
T-SQL |
SQL-like for JSON, MongoDB, Cassandra, etc. |
| Global Distribution |
manual geo-replication |
Native multi-region writes & reads |
| Latency & Throughput |
Moderate, optimized for transactional loads |
Ultra-low latency, high throughput |
| Consistency Options |
Strong (ACID) |
Multiple levels (strong to eventual) |
| Scalability |
Vertical & elastic pools |
Horizontal, auto-scaling via RUs |
| Pricing Model |
DTUs / vCores |
Request Units (RUs) |
| Best For |
Structured, transactional workloads |
Real-time, distributed, NoSQL workloads |
🧠 Which One Is “Best”?
It depends on your scenario:
Choose Azure SQL if you need:
- Relational integrity
- Complex joins and transactions
- Familiar SQL tooling
Choose Cosmos DB if you need:
- Global scale and low latency
- Flexible schema and rapid iteration
- Multi-model support for diverse data
For hybrid scenarios, some architectures use both: SQL for core business logic and Cosmos DB for real-time telemetry or user activity logs.
🧪 Best Practices for Azure SQL Database
- Use elastic pools for multi-tenant SaaS to optimize cost
- Enable Geo-replication for disaster recovery
- Use Query Performance Insight to monitor slow queries
- Apply row-level security and dynamic data masking
- Automate backups and long-term retention policies
🚀 Best Practices for Azure Cosmos DB
- Choose the right API (SQL, MongoDB, Cassandra) based on your app
- Use partition keys wisely to ensure scalability
- Optimize Request Units (RUs) to control cost
- Leverage multi-region writes for global apps
- Monitor with Azure Monitor and set alerts for RU consumption
