dynamodb
This skill provides guidance on AWS DynamoDB, a fully managed NoSQL database service. Use it when designing table schemas with partition and sort keys, implementing single-table design patterns, configuring global or local secondary indexes, choosing between on-demand and provisioned capacity modes, writing queries using boto3 or AWS CLI, managing throughput and auto-scaling, or diagnosing performance bottlenecks and scaling issues.
git clone --depth 1 https://github.com/itsmostafa/aws-agent-skills /tmp/dynamodb && cp -r /tmp/dynamodb/skills/dynamodb ~/.claude/skills/dynamodbSKILL.md
# AWS DynamoDB
Amazon DynamoDB is a fully managed NoSQL database service providing fast, predictable performance at any scale. It supports key-value and document data structures.
## Table of Contents
- [Core Concepts](#core-concepts)
- [Common Patterns](#common-patterns)
- [CLI Reference](#cli-reference)
- [Best Practices](#best-practices)
- [Troubleshooting](#troubleshooting)
- [References](#references)
## Core Concepts
### Keys
| Key Type | Description |
|----------|-------------|
| **Partition Key (PK)** | Required. Determines data distribution |
| **Sort Key (SK)** | Optional. Enables range queries within partition |
| **Composite Key** | PK + SK combination |
### Secondary Indexes
| Index Type | Description |
|------------|-------------|
| **GSI (Global Secondary Index)** | Different PK/SK, separate throughput, eventually consistent |
| **LSI (Local Secondary Index)** | Same PK, different SK, shares table throughput, strongly consistent option |
### Capacity Modes
| Mode | Use Case |
|------|----------|
| **On-Demand** | Unpredictable traffic, pay-per-request |
| **Provisioned** | Predictable traffic, lower cost, can use auto-scaling |
## Common Patterns
### Create a Table
**AWS CLI:**
```bash
aws dynamodb create-table \
--table-name Users \
--attribute-definitions \
AttributeName=PK,AttributeType=S \
AttributeName=SK,AttributeType=S \
--key-schema \
AttributeName=PK,KeyType=HASH \
AttributeName=SK,KeyType=RANGE \
--billing-mode PAY_PER_REQUEST
```
**boto3:**
```python
import boto3
dynamodb = boto3.resource('dynamodb')
table = dynamodb.create_table(
TableName='Users',
KeySchema=[
{'AttributeName': 'PK', 'KeyType': 'HASH'},
{'AttributeName': 'SK', 'KeyType': 'RANGE'}
],
AttributeDefinitions=[
{'AttributeName': 'PK', 'AttributeType': 'S'},
{'AttributeName': 'SK', 'AttributeType': 'S'}
],
BillingMode='PAY_PER_REQUEST'
)
table.wait_until_exists()
```
### Basic CRUD Operations
```python
import boto3
from boto3.dynamodb.conditions import Key, Attr
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('Users')
# Put item
table.put_item(
Item={
'PK': 'USER#123',
'SK': 'PROFILE',
'name': 'John Doe',
'email': 'john@example.com',
'created_at': '2024-01-15T10:30:00Z'
}
)
# Get item
response = table.get_item(
Key={'PK': 'USER#123', 'SK': 'PROFILE'}
)
item = response.get('Item')
# Update item
table.update_item(
Key={'PK': 'USER#123', 'SK': 'PROFILE'},
UpdateExpression='SET #name = :name, updated_at = :updated',
ExpressionAttributeNames={'#name': 'name'},
ExpressionAttributeValues={
':name': 'John Smith',
':updated': '2024-01-16T10:30:00Z'
}
)
# Delete item
table.delete_item(
Key={'PK': 'USER#123', 'SK': 'PROFILE'}
)
```
### Query Operations
```python
# Query by partition key
response = table.query(
KeyConditionExpression=Key('PK').eq('USER#123')
)
# Query with sort key condition
response = table.query(
KeyConditionExpression=Key('PK').eq('USER#123') & Key('SK').begins_with('ORDER#')
)
# Query with filter
response = table.query(
KeyConditionExpression=Key('PK').eq('USER#123'),
FilterExpression=Attr('status').eq('active')
)
# Query with projection
response = table.query(
KeyConditionExpression=Key('PK').eq('USER#123'),
ProjectionExpression='PK, SK, #name, email',
ExpressionAttributeNames={'#name': 'name'}
)
# Paginated query
paginator = dynamodb.meta.client.get_paginator('query')
for page in paginator.paginate(
TableName='Users',
KeyConditionExpression='PK = :pk',
ExpressionAttributeValues={':pk': {'S': 'USER#123'}}
):
for item in page['Items']:
print(item)
```
### Batch Operations
```python
# Batch write (up to 25 items)
with table.batch_writer() as batch:
for i in range(100):
batch.put_item(Item={
'PK': f'USER#{i}',
'SK': 'PROFILE',
'name': f'User {i}'
})
# Batch get (up to 100 items)
dynamodb = boto3.resource('dynamodb')
response = dynamodb.batch_get_item(
RequestItems={
'Users': {
'Keys': [
{'PK': 'USER#1', 'SK': 'PROFILE'},
{'PK': 'USER#2', 'SK': 'PROFILE'}
]
}
}
)
```
### Create GSI
```bash
aws dynamodb update-table \
--table-name Users \
--attribute-definitions AttributeName=email,AttributeType=S \
--global-secondary-index-updates '[
{
"Create": {
"IndexName": "email-index",
"KeySchema": [{"AttributeName": "email", "KeyType": "HASH"}],
"Projection": {"ProjectionType": "ALL"}
}
}
]'
```
### Conditional Writes
```python
from botocore.exceptions import ClientError
# Only put if item doesn't exist
try:
table.put_item(
Item={'PK': 'USER#123', 'SK': 'PROFILE', 'name': 'John'},
ConditionExpression='attribute_not_exists(PK)'
)
except ClientError as e:
if e.response['Error']['Code'] == 'ConditionalCheckFailedException':
print("Item already exists")
# Optimistic locking with version
table.update_item(
Key={'PK': 'USER#123', 'SK': 'PROFILE'},
UpdateExpression='SET #name = :name, version = version + :inc',
ConditionExpression='version = :current_version',
ExpressionAttributeNames={'#name': 'name'},
ExpressionAttributeValues={
':name': 'New Name',
':inc': 1,
':current_version': 5
}
)
```
## CLI Reference
### Table Operations
| Command | Description |
|---------|-------------|
| `aws dynamodb create-table` | Create table |
| `aws dynamodb describe-table` | Get table info |
| `aws dynamodb update-table` | Modify table/indexes |
| `aws dynamodb delete-table` | Delete table |
| `aws dynamodb list-tables` | List all tables |
### Item Operations
| Command | Description |
|---------|-------------|
| `aws dynamodb put-item` | Create/replace item |
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