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Database Services

Notes about AWS Database Services​

database_services

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You can download these notes as pdf from here.

1. Amazon RDS (Relational Database Service)​

  • Managed Database Service: Simplifies the setup, operation, and scaling of a relational database.
  • Supported Engines: MySQL, PostgreSQL, MariaDB, Oracle, SQL Server, and Amazon Aurora.
  • Multi-AZ Deployments: Provides high availability and automatic failover.
  • Read Replicas: Improve read performance and scalability.
  • Automated Backups: Daily backups, snapshots, and point-in-time recovery.
  • Monitoring: Use CloudWatch for metrics and performance insights for detailed performance analysis.
  • Security: Network isolation with VPC, encryption at rest and in transit, IAM roles for access management.

2. Amazon Aurora​

  • MySQL and PostgreSQL-Compatible: High performance and availability with full compatibility.
  • High Availability: Automatic failover, continuous backup to S3, replication across three Availability Zones.
  • Performance: 5x throughput of standard MySQL and 3x of PostgreSQL.
  • Serverless Option: Scales automatically based on application needs.
  • Global Databases: Enables a single database to span multiple AWS regions.

3. Amazon DynamoDB​

  • NoSQL Database: Fully managed, key-value and document database.
  • Scalability: Automatically scales throughput capacity, offers on-demand mode for instant scaling.
  • Performance: Single-digit millisecond response times.
  • Data Models: Tables, items, and attributes with support for document and key-value store models.
  • Indexes: Global Secondary Indexes (GSI) and Local Secondary Indexes (LSI) for query flexibility.
  • DynamoDB Streams: Capture changes to items in a table for real-time processing.
  • DAX: In-memory caching for DynamoDB, providing microsecond latency.

4. Amazon ElastiCache​

  • In-Memory Data Store: Fully managed Redis or Memcached service.
  • Use Cases: Caching, session management, real-time analytics.
  • Scalability: Scale-out, sharding, replication.
  • High Availability: Multi-AZ with automatic failover for Redis.
  • Performance: Sub-millisecond response times, high throughput.

5. Amazon MemoryDB for Redis​

  • Fully Managed Redis-Compatible Database: Provides Redis-compatible in-memory database service for real-time applications.
  • High Availability: Multi-AZ replication with automatic failover.
  • Durability: Data is replicated across multiple nodes and backed up to disk.
  • Performance: Designed for high throughput and low latency.
  • Security: Supports encryption at rest and in transit, VPC isolation, and IAM integration.
  • Scalability: Easily scale read and write capacity to meet application demands.

Key Concepts and Best Practices​

  • High Availability: Implement Multi-AZ deployments and read replicas where applicable.
  • Scalability: Use features like auto-scaling for DynamoDB, Aurora's serverless option, and Redshift's ability to scale compute and storage independently.
  • Backup and Recovery: Regularly back up databases, use automated backups and snapshots.
  • Security: Encrypt data at rest and in transit, use IAM for access control, isolate databases in VPCs.
  • Monitoring and Performance: Use CloudWatch for monitoring metrics, performance insights for RDS and Aurora, and DynamoDB's performance tools.
  • Cost Management: Choose the right instance types and storage options, leverage reserved instances for long-term savings, and monitor usage to avoid over-provisioning.
  • Data Integrity: Use transaction management and data replication features to ensure consistency and durability.
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