Amazon Aurora

• Aurora is a proprietary technology from AWS (not open sourced)
• Postgres and MySQL are both supported as Aurora DB (that means your drivers will work as if Aurora was a Postgres or MySQL database)
• Aurora is “AWS cloud optimized” and claims 5x performance improvement over MySQL on RDS, over 3x the performance of Postgres on RDS
• Aurora storage automatically grows in increments of 10GB, up to 128 TB.
• Aurora can have up to 15 replicas and the replication process is faster than MySQL (sub 10 ms replica lag)
• Fail over in Aurora is instantaneous. It’s HA (High Availability) native.
• Aurora costs more than RDS (20% more) – but is more efficient

Amazon Aurora Serverless

• Automated database instantiation and auto-scaling based on actual usage
• Good for infrequent, intermittent or unpredictable workloads
• No capacity planning needed
• Pay per second, can be more cost-effective

Aurora High Availability and Read Scaling

• 6 copies of your data across 3 AZ:
• 4 copies out of 6 needed for writes
• 3 copies out of 6 need for reads
• Self healing with peer-to-peer replication
• Storage is striped across 100s of volumes
• One Aurora Instance takes writes (master)
• Automated failover for master in less than 30 seconds
• Master + up to 15 Aurora Read Replicas serve reads
• Support for Cross Region Replication

Aurora DB clusters

Features of Aurora

• Automatic fail-over
• Backup and Recovery
• Isolation and security
• Industry compliance
• Push-button scaling
• Automated Patching with Zero Downtime
• Advanced Monitoring
• Routine Maintenance
• Backtrack: restore data at any point of time without using backups

Aurora Replicas - Auto Scaling

Aurora Custom Endpoints

• Define a subset of Aurora Instances as a Custom Endpoint
• Example: Run analytical queries on specific replicas
• The Reader Endpoint is generally not used after defining Custom Endpoints

Global Aurora

• Aurora Cross Region Read Replicas:
  • Useful for disaster recovery
  • Simple to put in place
• Aurora Global Database (recommended):
  • 1 Primary Region (read / write)
  • Up to 5 secondary (read-only) regions, replication lag is less than 1 second
  • Up to 16 Read Replicas per secondary region
  • Helps for decreasing latency
  • Promoting another region (for disaster recovery) has an RTO of < 1 minute
  • Typical cross-region replication takes less than 1 second

Aurora Machine Learning Integration

• Enables you to add ML-based predictions to your applications via SQL
• Simple, optimized, and secure integration between Aurora and AWS ML services
• Supported services
• Amazon SageMaker (use with any ML model)
• Amazon Comprehend (for sentiment analysis)
• You don’t need to have ML experience
• Use cases: fraud detection, ads targeting, sentiment analysis, product recommendations

Aurora Backup

• Automated backups
  • 1 to 35 days (cannot be disabled)
  • point-in-time recovery in that timeframe
• Manual DB Snapshots
  • Manually triggered by the user
  • Retention of backup for as long as you want

Aurora Database Cloning

• Create a new Aurora DB Cluster from an existing one
• Faster than snapshot & restore
• Uses copy-on-write protocol
• Initially, the new DB cluster uses the same data volume as the original DB cluster (fast and efficient – no copying is needed)
• When updates are made to the new DB cluster data, then additional storage is allocated and data is copied to be separated
• Very fast & cost-effective
• Useful to create a “staging” database from a “production” database without impacting the production database