Lower Administrative Burden
- No need to provision infrastructure
- No need to install and maintain database software
- Single console and API for managing all relational databases
- Built-in security and monitoring
Amazon Rds
Amazon RDS
Section titled “Amazon RDS”Amazon RDS is a fully managed relational database service that you can use to set up, operate, and scale relational databases in the cloud.
Overview
Section titled “Overview”Amazon RDS is a managed relational database service to deploy and scale relational databases. It automates routine database tasks such as provisioning, patching, backup, recovery, failure detection, and repair without needing to provision infrastructure or maintain software.
Supported Database Engines
Section titled “Supported Database Engines”- Amazon Aurora with MySQL compatibility
- Amazon Aurora with PostgreSQL compatibility
- Amazon RDS for MySQL
- Amazon RDS for MariaDB
- Amazon RDS for PostgreSQL
- Amazon RDS for Oracle
- Amazon RDS for SQL Server
Amazon RDS uses Amazon Elastic Block Store (Amazon EBS) volumes for database and log storage, and you can scale the storage capacity allocated to your database instance.
Benefits of Amazon RDS
Section titled “Benefits of Amazon RDS”Highly Scalable
- Scale compute and memory resources with few mouse clicks or API call
- Selection of instance types optimized for different use cases
- Flexibility to choose appropriate mix of resources
Available and Durable
- Multi-AZ deployment for high availability with automated failover
- Read replicas for scaling read-heavy workloads
- Synchronously replicated secondary database
Secure and Compliant
- Run database instances in Amazon VPC for isolation
- Firewall settings and network access control
- Encryption at rest and in transit
- HIPAA eligibility and compliance readiness
RDS Database Architecture
Section titled “RDS Database Architecture”Amazon RDS facilitates deployment and maintenance of relational databases in the cloud by managing a specialized EC2 instance that provides computing capacity.
Key Components
Section titled “Key Components”- RDS instances: Isolated database environments that can contain multiple user-created databases
- Database engine: Allows storing, sorting, and retrieving data
- EBS volumes: Used for database and log storage with scalable capacity
Aurora
Section titled “Aurora”Aurora is a MySQL and PostgreSQL-compatible RDBMS built for the cloud:
Performance Benefits
Section titled “Performance Benefits”- Up to 5x faster than standard MySQL databases
- Up to 3x faster than standard PostgreSQL databases
- Security, availability, and reliability of commercial databases at approximately 1/10th the cost
Key Features
Section titled “Key Features”- Fully managed by Amazon RDS
- Automates hardware provisioning, database setup, patching, and backups
- Distributed, fault-tolerant, self-healing storage system
- Auto scales up to 64 TB per database instance
- Up to 15 low-latency read replicas
- Point-in-time recovery and continuous backup to Amazon S3
- Replication across three Availability Zones
Aurora Database Clusters
Section titled “Aurora Database Clusters”An Aurora database cluster includes one or more database instances and a cluster volume that manages data for those instances.
Cluster Components
Section titled “Cluster Components”Primary Database Instance:
- Supports read and write operations
- Performs all data modifications to the cluster volume
- Each Aurora DB cluster has one primary DB instance
Aurora Replicas:
- Connect to same storage volume as primary DB instance
- Support only read operations
- Up to 15 Aurora replicas per cluster
- Located in separate Availability Zones for high availability
- Automatic failover in case primary becomes unavailable
- Can specify failover priority
- Offload read workloads from primary instance
Aurora Serverless
Section titled “Aurora Serverless”Aurora Serverless is an on-demand, auto scaling configuration for Aurora where the database automatically starts up, shuts down, and scales capacity based on application needs.
Use Cases
Section titled “Use Cases”Running workloads with sudden and unpredictable increases in activity. Database automatically scales to meet peak load and scales back down when activity decreases.
Deploying new applications when unsure about DB instance size needed. Set up cluster and have database auto scale to capacity requirements.
Create DB instances with low minimum capacity and high maximum capacity. Instances scale down when not in use to avoid unnecessary charges.
Avoid administrative overhead of modifying DB instance classes. Determine appropriate minimum and maximum capacity by running workload and checking actual scaling.
Features
Section titled “Features”- Hands-off capacity management
- Fine-grained scaling
- Can modify existing DB instances from provisioned to Aurora Serverless v2 or vice versa
- Can use Aurora Serverless v2 instances along with provisioned instances in existing or new clusters
Use Case: Banking Transactions
Section titled “Use Case: Banking Transactions”Amazon RDS is suitable for online transaction processing (OLTP) that stores and updates transactional data reliably and efficiently in high volumes.
Banking transaction example showing transactional data structure:
| Transaction ID | Date | Transaction Description | Transaction Type | Transaction Amount |
|---|---|---|---|---|
| 0079834514 | 2023-11-05 | Utility | Withdrawal | 100.00 |
| 0079834513 | 2023-11-05 | Employer name | Direct deposit | 1000.00 |
| 0079834512 | 2023-11-04 | Interest payment | Deposit | 0.07 |
Each transaction has unique identifier with data including transaction date, description, type, and amount recorded for each transaction.
Instance Types and Sizing
Section titled “Instance Types and Sizing”Amazon RDS provides instance types optimized for different relational database use cases with varying combinations of CPU, memory, storage, and networking capacity.
Instance Type Categories
Section titled “Instance Type Categories”General Purpose (T4g, T3, M6g, M5):
- Suitable for CPU-intensive workloads
- Moderate CPU usage with temporary spikes
Memory-Optimized (R6g, R5, X2g, X1E):
- Suitable for query-intensive workloads
- High connection counts
Sizing Example
Section titled “Sizing Example”| Instance Type | Memory (GiB) | vCPU |
|---|---|---|
| db.m6g.large | 8 | 2 |
| db.r6g.large | 16 | 2 |
| db.m6g.xlarge | 16 | 4 |
| db.r6g.xlarge | 32 | 4 |
When upgrading, first identify the issue: if m6g.large needs upgrade, determine if it needs more memory (r6g.large) or CPU (m6g.xlarge).
Security Best Practices
Section titled “Security Best Practices”VPC Deployment
Run DB instance in custom and private VPC for greatest possible network access control
IAM Policies
Use IAM policies to assign permissions for managing Amazon RDS resources
Security Groups
Control connecting IP addresses and resources through security groups
SSL/TLS Connections
Use SSL or TLS connections with database instances running supported engines
Encryption
Encrypt database instances and snapshots at rest with AWS KMS key
Database Security Features
Use security features of database engine to control database access
Security is a shared responsibility between you and AWS. AWS protects infrastructure, while you are responsible for security in the cloud including managing access to RDS resources and databases on instances.