Amazon Aurora

Amazon Aurora is AWS's cloud-native relational database, MySQL- and PostgreSQL-compatible, delivered through Amazon RDS. It combines the familiarity of open-source engines with a re-architected storage layer that distributes data across three Availability Zones with six-way replication — giving higher throughput, faster recovery, and near-zero data loss.

Key Features:

• Distributed Storage: 10 GB segments replicated 6 ways across 3 AZs; storage auto-scales up to 128 TiB (Aurora MySQL/PostgreSQL) without downtime.
• Aurora Replicas: Up to 15 low-latency read replicas sharing the same storage volume; failover to a replica typically under 30 seconds.
• Aurora Serverless v2: On-demand auto-scaling capacity (measured in ACUs) that scales in seconds, ideal for variable or unpredictable workloads.
• Global Database: Single primary region with up to 5 read-only secondary regions; cross-region replication via dedicated infrastructure with sub-second lag and ~1-minute RTO on regional failure.
• Backtrack (MySQL): Rewind the database in place to a previous point in time (up to 72 hours) without restoring a backup.
• Parallel Query: Push query processing down into the distributed storage layer for large analytical scans.
• Zero-ETL to Redshift: Continuous replication of Aurora tables into Amazon Redshift for analytics without building pipelines.

Aurora vs. RDS (MySQL/Postgres):

• Performance: Aurora typically delivers 3–5× MySQL throughput and 2–3× PostgreSQL throughput on the same hardware.
• Availability: 6-way replication across 3 AZs vs. RDS's single-AZ primary + Multi-AZ standby.
• Cost: Aurora is ~20% more expensive than equivalent RDS, but the storage model often reduces total cost at scale.
• Choose RDS for plain MySQL/PostgreSQL/MariaDB/Oracle/SQL Server workloads; choose Aurora when you need Aurora-specific features (Serverless v2, Global Database, Backtrack, Parallel Query, Zero-ETL).

Common Use Cases:

• High-throughput OLTP workloads that outgrow vanilla RDS.
• SaaS applications needing multi-tenant scale with per-tenant read replicas.
• Global applications with sub-second cross-region read latency requirements.
• Variable workloads (dev/test, spiky traffic) on Aurora Serverless v2.
• Analytics on operational data via Zero-ETL to Redshift.