In today's cloud-first world, applications generate more data, require higher uptime, and demand instant scalability. Microsoft Azure provides a rich ecosystem of fully managed database services designed to support virtually any workload—from transactional systems and real-time analytics to globally distributed web apps and high-performance AI pipelines.
If you're planning or evaluating a cloud migration, it's helpful to understand Azure's major database offerings, their strengths, and the ideal use cases for each. This guide breaks down the key Azure database services to help you make an informed decision.
1. Azure SQL DatabaseAzure SQL Database is a fully managed Platform-as-a-Service (PaaS) relational database based on the Microsoft SQL Server engine.
Key Features- Automatic backups, patching, and updates
- Built-in high availability
- Intelligent performance tuning powered by AI
- Multiple deployment options (single database, elastic pools, serverless)
- Traditional OLTP workloads
- SaaS applications
- Systems needing low-maintenance SQL Server compatibility
If you want SQL Server capabilities without managing hardware, OS, or upgrades, Azure SQL Database is the go-to option.
2. Azure SQL Managed InstanceAzure SQL Managed Instance (MI) offers nearly full compatibility with on-prem SQL Server, making migrations simpler.
Key Features- 100% SQL Server engine compatibility
- Support for SQL Agent, cross-database queries, and linked servers
- Virtual network (VNet) isolation
- Automated patching and backups
- Lift-and-shift migrations from on-prem SQL Server
- Legacy applications requiring SQL Server features not available in Azure SQL Database
Choose Managed Instance when you need SQL Server compatibility but still want a fully managed cloud database service.
3. Azure Cosmos DBCosmos DB is a globally distributed, NoSQL database designed for massive scale, low latency, and multi-model data.
Key Features- Global distribution with single-digit millisecond latency
- Five consistency levels
- Multi-model support (Core SQL/Document, MongoDB API, Cassandra API, Gremlin, Table API)
- Horizontal scalability and automatic indexing
- Large-scale, high-traffic web and mobile applications
- IoT and telemetry data
- Real-time analytics
- Globally distributed systems
If your application needs high write throughput, low latency, or multi-region availability, Cosmos DB is the ideal option.
4. Azure Database for PostgreSQLAzure offers a fully managed PostgreSQL service in two flavors: Single Server and Flexible Server.
Key Features- Community PostgreSQL compatibility
- High availability and automated maintenance
- Flexible configurations, including zone-redundant HA
- Support for extensions (e.g., PostGIS, pgcrypto)
- Applications built on open-source PostgreSQL
- Geospatial analytics
- Enterprise applications needing relational structure + extensibility
Choose when you want the power of PostgreSQL without managing servers.
5. Azure Database for MySQLA fully managed MySQL database optimized for performance and scalability.
Key Features- High availability out of the box
- Automatic backups and patching
- Flexible compute tiers
- Support for MySQL community tools
- LAMP stack applications
- Open-source CMS platforms (WordPress, Drupal, Joomla)
- E-commerce apps requiring reliable OLTP
If your applications rely on MySQL or you need a cost-effective relational database, this service fits well.
6. Azure Database for MariaDBMariaDB is another open-source relational database supported as a fully managed Azure PaaS service.
Key Features- Community MariaDB compatibility
- Automated backups and maintenance
- Built-in HA and dynamic scaling
- Existing MariaDB applications
- Organizations standardizing on open-source DBs
Good for teams already using MariaDB that want to shift to managed cloud infrastructure.
7. Azure SQL EdgeA lightweight SQL engine designed for IoT and edge computing scenarios.
Key Features- Runs on ARM and x64 devices
- Supports streaming, time-series, and in-built ML
- Offline and connected modes
- IoT solutions
- Industrial automation
- Real-time edge analytics
Pick SQL Edge when you need database processing close to sensors or devices.
8. Azure Synapse AnalyticsA cloud-scale analytics service combining data warehousing and big data capabilities.
Key Features- Massively parallel processing (MPP)
- Integrated with Azure Data Lake Storage
- Power BI, Spark, and SQL engines in one platform
- Time-to-insight optimization
- Enterprise data warehouses
- Big data analytics and BI workloads
- Complex ETL/ELT pipelines
Choose Synapse when you need analytics at scale, not high-velocity transactional processing.
9. Azure DatabricksA unified analytics platform powered by Apache Spark.
Key Features- High-performance Spark clusters
- Collaborative notebooks
- MLflow integration for machine learning lifecycle management
- Big data processing
- Data engineering pipelines
- Machine learning and AI workloads
Great for teams doing large-scale data transformation, machine learning, or AI experimentation.
How to Choose the Best Azure Database for Your Application| Requirement | Recommended Azure Service |
|---|---|
| Traditional relational OLTP | Azure SQL Database / Managed Instance |
| Massive scale NoSQL | Azure Cosmos DB |
| Open-source relational (PostgreSQL/MySQL/MariaDB) | Azure Database for PostgreSQL/MySQL/MariaDB |
| Global distribution & low latency | Cosmos DB |
| Data warehousing | Azure Synapse Analytics |
| High-performance analytics & ML | Azure Databricks |
| Edge and IoT | Azure SQL Edge |
Azure's database ecosystem is one of the broadest and most flexible in the cloud market. Whether you're modernizing legacy systems, building cloud-native apps, or designing a global analytics platform, Azure has a database service tailored to your needs.