AWS offers a broad portfolio of managed database services so you can match the right database engine and model to your application's needs. Managed services handle patching, backups, replication, and failover — freeing you from database administration work.
Amazon RDS — Relational Database Service
RDS provides managed relational databases supporting six engines: MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server, and Amazon Aurora.
Key RDS Features
- Automated backups: Daily snapshots + transaction logs. Restore to any point in the retention window (up to 35 days).
- Multi-AZ deployments: Synchronous standby replica in a second AZ. Automatic failover in ~60 seconds. Use for production high availability.
- Read replicas: Asynchronous copies for read-heavy workloads. Up to 5 replicas (MySQL, PostgreSQL). Can be in different regions.
- Encryption: At-rest (AWS KMS) and in-transit (TLS).
- Parameter groups / option groups: Customise DB engine settings.
When to Use RDS
Use RDS when you need traditional SQL with ACID transactions, structured schemas, and complex JOINs — such as e-commerce, ERP, or any application that already uses a relational database.
Amazon Aurora
Aurora is AWS's cloud-native relational database — compatible with MySQL and PostgreSQL but rebuilt for cloud performance and availability.
- Up to 5× faster than MySQL, 3× faster than PostgreSQL
- Storage auto-scales from 10 GB to 128 TB in 10 GB increments
- Data is automatically replicated 6 ways across 3 AZs
- Failover typically completes in under 30 seconds
- Aurora Serverless v2: Scales capacity automatically in fine-grained increments; ideal for variable workloads
- Aurora Global Database: Replicates to up to 5 secondary regions for disaster recovery
Amazon DynamoDB
DynamoDB is a fully managed serverless NoSQL database — key-value and document model. It's the go-to AWS database when you need:
- Single-digit millisecond performance at any scale
- Automatic horizontal scaling
- No schema management
- Serverless billing (pay per read/write, or provision capacity)
Key concepts:
- Table: Collection of items (rows)
- Item: A single record (like a row); up to 400 KB
- Primary key: Partition key alone, or partition key + sort key
- GSI (Global Secondary Index): Query on non-primary-key attributes
- DynamoDB Streams: Change data capture feed for Lambda triggers
- DAX (DynamoDB Accelerator): In-memory cache, microsecond read latency
Amazon ElastiCache
ElastiCache provides managed in-memory caching. It sits in front of a database to serve frequently read data at microsecond speed, dramatically reducing database load.
- Redis: More features — persistence, pub/sub, sorted sets, Lua scripting. Cluster mode for horizontal scaling.
- Memcached: Simple, high-throughput caching. Multi-threaded. No persistence.
Other Database Services
| Service | Type | Use Case |
|---|---|---|
| Amazon Redshift | Data warehouse (columnar SQL) | Analytics, business intelligence |
| Amazon DocumentDB | MongoDB-compatible document DB | JSON documents, content management |
| Amazon Neptune | Graph database | Social networks, fraud detection, knowledge graphs |
| Amazon Keyspaces | Managed Apache Cassandra | Wide-column, time-series |
| Amazon Timestream | Time-series database | IoT sensor data, metrics |
| Amazon QLDB | Ledger database | Immutable audit trail, financial records |
Choosing the Right Database
| Requirement | Service |
|---|---|
| Traditional SQL with transactions | RDS or Aurora |
| Maximum performance SQL | Aurora |
| Serverless NoSQL, unlimited scale | DynamoDB |
| Caching layer | ElastiCache |
| Analytics / BI | Redshift |
| Document store | DocumentDB |
Next: networking in AWS — VPCs, subnets, security groups, and how traffic flows in the cloud.