Databases on AWS

AWS offers a wide range of managed database services: relational (RDS), NoSQL (DynamoDB), caching (ElastiCache), and more. The key advantage is that AWS handles backups, patching, replication, and scaling.

Analogy: Managed databases are like hiring a professional chef instead of cooking yourself. AWS takes care of all the hard work — backups, updates, failovers — so you just use the database.

Database Options Overview

flowchart TB
    Q["What kind of data?"] --> Relational{"Structured<br/>relationships?"}

    Relational -->|"Yes (SQL, tables, joins)"| RDS["RDS — Relational<br/>PostgreSQL, MySQL, MariaDB,<br/>SQL Server, Oracle"]
    Relational -->|"No (flexible schema)"| NoSQL{"Key-value or<br/>document?"}

    NoSQL -->|"Key-value<br/>High scale, low latency"| DynamoDB["DynamoDB<br/>Managed NoSQL"]
    NoSQL -->|"Document<br/>MongoDB-like"| DocumentDB["DocumentDB<br/>MongoDB compatible"]

    Q --> Cache{"Caching?"}
    Cache -->|"Yes, speed up reads"| ECache["ElastiCache<br/>Redis / Memcached"]

    style Q fill:#f59e0b,color:#fff
    style RDS fill:#3b82f6,color:#fff
    style DynamoDB fill:#7c3aed,color:#fff
    style DocumentDB fill:#059669,color:#fff
    style ECache fill:#ef4444,color:#fff

RDS — Relational Database Service

Supports 6 database engines as managed services:

Engine	Best For
PostgreSQL	Advanced relational apps, geospatial
MySQL	Web apps, WordPress, open-source stacks
MariaDB	MySQL-compatible, community-driven
SQL Server	Enterprise .NET apps
Oracle	Enterprise Oracle ecosystem
Aurora	AWS-native, 5x faster than MySQL, 3x faster than Postgres

# Create a PostgreSQL RDS instance
aws rds create-db-instance \
    --db-instance-identifier my-db \
    --db-instance-class db.t3.micro \
    --engine postgres \
    --master-username admin \
    --master-user-password secret123 \
    --allocated-storage 20

RDS features:

Automated backups (point-in-time recovery)
Multi-AZ (synchronous standby replica)
Read replicas (scale reads)
Automated patching

DynamoDB — NoSQL Database

DynamoDB is a fully managed, key-value + document database with single-digit millisecond performance at any scale.

import boto3
dynamodb = boto3.resource('dynamodb')

# Create table
table = dynamodb.create_table(
    TableName='Users',
    KeySchema=[{'AttributeName': 'userId', 'KeyType': 'HASH'}],
    AttributeDefinitions=[{'AttributeName': 'userId', 'AttributeType': 'S'}],
    BillingMode='PAY_PER_REQUEST'
)

# Put item
table.put_item(Item={
    'userId': '123',
    'name': 'Alice',
    'email': 'alice@example.com',
    'age': 30
})

# Get item
response = table.get_item(Key={'userId': '123'})
print(response['Item'])

Feature	Detail
Performance	Consistent single-digit ms latency
Scaling	Auto-scales — no limits
Pricing	Pay per read/write unit (on-demand or provisioned)
Consistency	Eventually consistent by default (strong optional)
Backups	Automated (PITR) and on-demand

DynamoDB vs RDS — Quick Decision

Need This	Use
SQL queries, joins, complex relationships	RDS (PostgreSQL/MySQL)
High-scale, low-latency key-value access	DynamoDB
Complex transactions across tables	RDS
Serverless, auto-scaling database	DynamoDB
Existing app needs MySQL/Postgres	RDS
Shopping cart, session data, user profiles	DynamoDB

ElastiCache — In-Memory Caching

ElastiCache provides managed Redis and Memcached — perfect for caching, session stores, and real-time data.

See the Redis track for detailed Redis concepts.

# Create a Redis cluster
aws elasticache create-cache-cluster \
    --cache-cluster-id my-cache \
    --cache-node-type cache.t3.micro \
    --engine redis

In Simple Words

RDS = managed SQL databases (PostgreSQL, MySQL) — for structured relational data
DynamoDB = managed NoSQL — for high-scale, low-latency key-value data
ElastiCache = managed Redis — for caching and real-time data
Use RDS for complex queries; DynamoDB for massive scale
AWS handles backups, patching, replication — you just use the database