Azure SQL Database vs AWS RDS | Generated by AI

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Overview

Azure SQL Database and Amazon RDS are both fully managed relational database services designed to simplify database administration, scaling, and maintenance. Azure SQL Database is Microsoft’s PaaS offering focused primarily on SQL Server (with equivalents like Azure Database for MySQL and PostgreSQL for other engines), while AWS RDS is Amazon’s multi-engine service supporting SQL Server, MySQL, PostgreSQL, Oracle, MariaDB, and proprietary Aurora variants. The choice often depends on your ecosystem (Microsoft integration favors Azure; multi-cloud or diverse engines favor AWS), workload type, and migration needs. Below is a side-by-side comparison across key dimensions.

Category Azure SQL Database AWS RDS
Supported Engines Primarily SQL Server (always latest version, e.g., 2022); separate services for MySQL, PostgreSQL, and MariaDB. No direct support for Oracle in managed form (use VMs). Multi-engine: SQL Server (versions 2012–2019), MySQL, PostgreSQL, Oracle, MariaDB, and Aurora (MySQL/PostgreSQL-compatible with higher performance).
Scalability Highly granular: DTU model for predictable performance tuning; vCore for compute-based scaling; elastic pools for shared resources across databases; serverless option auto-pauses idle DBs. Seamless, low-downtime scaling; supports up to 100 TB. Instance-based scaling (add CPU/RAM/IOPS); Aurora Serverless for auto-scaling; read replicas for read-heavy loads. Up to 128 TB storage; some downtime during scale-up (schedulable). Better for legacy version-specific scaling.
Performance Fine-tuned via DTU/vCore; readable secondaries for offloading reports; potential gateway latency in single-DB mode (use Managed Instance for direct connectivity). Strong for Microsoft-integrated apps. Predictable hardware-tied performance; high memory:vCPU ratios; lacks native read replicas for SQL Server (use AlwaysOn). Excels in high-throughput scenarios like real-time requests.
Pricing Pay-per-use (DTU/vCore/storage); elastic pools optimize costs; up to 55% dev/test savings; BYOL for Managed Instance; serverless bills only active time. Starts ~$5/month for basic. Use Azure Pricing Calculator. Pay-for-use (instance/storage/IOPS); reserved instances for 20–30% savings; no BYOL for SQL Server; cheaper long-term (~20% less than Azure after 2–3 years). Starts ~$0.017/hour for small instances. Use AWS Pricing Calculator.
Availability & Backup 99.99% SLA; geo-replication; automated backups (up to 10 years retention); point-in-time restore. 99.95–99.99% SLA (multi-AZ); automated snapshots; read replicas for HA; cross-region replication.
Security Built-in encryption (TDE, Always Encrypted); Azure AD integration; advanced threat protection; compliance (HIPAA, PCI DSS). Strong SaaS model reduces breach risks. Encryption at rest/transit (KMS); IAM authentication; VPC isolation; compliance certifications. Effective for multi-engine security but mixed reviews on customization.
Management & Features Auto-patching/upgrades; integrates with Microsoft Fabric for analytics/AI; elastic jobs for cross-DB tasks; no DBA needed for basics. Easier for .NET/Visual Studio users. Automated backups/patching; CloudWatch monitoring; Performance Insights; proxies for connection pooling. Better for DevOps automation and legacy SQL versions.
Pros Seamless Microsoft ecosystem integration; latest SQL features; cost-effective serverless/elastic options; high ROI via hybrid benefits. Multi-engine flexibility; stable for large-scale/diverse workloads; easier lift-and-shift migrations; strong automation for backups/scaling.
Cons Gateway latency in single-DB; pricing complexity; limited older SQL version support (use VMs). No latest SQL Server (2022); no BYOL; occasional integration/support issues; lacks native CDC for some engines.

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