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Module 7 — Databases

Status: ⬜ upcoming (next) · Domain 3 · We'll deepen this and build a visual page when we study it.

Topic outline (starting reference)

• Amazon RDS — managed relational database (handles patching, backups, HA). Engines: MySQL, PostgreSQL, MariaDB, Oracle, SQL Server. Multi-AZ = standby copy for failover (HA); Read Replicas = scale reads.
• Amazon Aurora — AWS's own relational engine, MySQL/PostgreSQL-compatible, ~5x/3x faster, fully managed, auto-scaling storage. Pricier but high performance.
• Amazon DynamoDB — managed NoSQL key-value/document DB. Serverless, single-digit-millisecond latency, virtually unlimited scale. No schema.
• Amazon Redshift — data warehouse for analytics / OLAP (query petabytes with SQL). Think reporting, not transactions.
• Amazon ElastiCache — managed in-memory cache (Redis or Memcached) to speed up reads.
• Amazon MemoryDB for Redis — durable in-memory database.
• DynamoDB Accelerator (DAX) — in-memory cache for DynamoDB (microsecond reads).
• Migration: DMS (Database Migration Service — move DBs to AWS, minimal downtime) · SCT (Schema Conversion Tool — convert between engines).

Likely exam framing

• "Managed relational DB" → RDS. "MySQL/Postgres-compatible, high performance" → Aurora.
• "NoSQL, key-value, serverless, millisecond scale" → DynamoDB.
• "Data warehouse / analytics / BI queries" → Redshift.
• "Speed up a database with caching" → ElastiCache (or DAX for DynamoDB).
• "Migrate a database to AWS" → DMS (+ SCT if changing engine).