DynamoDB

📌 1. What is DynamoDB?

Amazon DynamoDB is a fully managed NoSQL database service that delivers:

• Single-digit millisecond latency

• Auto-scaling read/write throughput

• Built-in replication, encryption, and backup

• Serverless, with no provisioning required

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🗃️ 2. Core Concepts

Concept	Description
Table	Collection of items (like a SQL table)
Item	A row in the table
Attribute	A column or field in an item
Primary Key	Uniquely identifies an item (Partition Key or Partition + Sort Key)
Secondary Index	Enables querying by non-key attributes
Provisioned / On-Demand	Controls read/write capacity mode

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🔑 3. Primary Key Types

Key Type	Description	Example
Partition Key	Simple key (hashed)	UserID
Partition + Sort Key	Composite key (hashed + range)	UserID + Date

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🔍 4. Query vs Scan

Operation	Description	Performance
Query	Retrieve items by primary or secondary key	Efficient
Scan	Reads every item in the table	Costly

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🧱 5. Capacity Modes

Mode	Description	Use Case
Provisioned	Set read/write units manually	Predictable workloads
On-Demand	Scales automatically based on traffic	Unpredictable or spiky loads

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🧠 6. DynamoDB Read/Write Units

Operation	Definition
1 RCU (Read)	1 strongly consistent read per second for 4 KB
1 WCU (Write)	1 write per second for 1 KB

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🔄 7. Global Secondary Index (GSI)

• Allows queries using non-key attributes

• Supports different partition/sort key

• Must be defined when creating the table or later

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⏱️ 8. DynamoDB Streams

• Captures table change logs (insert/update/delete)

• Use with AWS Lambda for event-driven architecture

• Retention: 24 hours

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🔐 9. DynamoDB Security

Feature	Description
IAM Policies	Fine-grained access control
KMS Encryption	Encryption at rest (AWS-owned or CMK)
VPC Endpoints	Secure private access via VPC

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♻️ 10. Backup & Restore

• On-demand backup and point-in-time restore

• Up to 35 days of PITR

• Cross-region backups supported

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📈 11. Monitoring & Metrics

Tool	Monitored Metrics
CloudWatch	ThrottledRequests, ReadThrottleEvents
DynamoDB Console	Capacity usage, Item count, Latency
AWS X-Ray	Query tracing and debugging

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🧪 12. Use Cases

✅ Real-time gaming
✅ E-commerce carts
✅ Serverless backends
✅ Leaderboards
✅ Sensor data collection
✅ IAM session tokens (like AWS does internally)

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⚙️ 13. Creating DynamoDB Table (Console)

1. Go to DynamoDB Console

2. Click "Create Table"

3. Enter:

   • Table name (e.g., Users)

   • Primary key: UserID (partition) or UserID + Timestamp (composite)

4. Choose:

   • On-demand or provisioned mode

   • Encryption (default: AWS-owned KMS)

5. Click Create

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🛠️ 14. Terraform Example

resource "aws_dynamodb_table" "users" {
  name           = "Users"
  billing_mode   = "PAY_PER_REQUEST"
  hash_key       = "UserID"

  attribute {
    name = "UserID"
    type = "S"
  }

  tags = {
    Environment = "dev"
    Project     = "myapp"
  }
}

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🧠 15. Best Practices

✅ Use partition key with high cardinality
✅ Avoid hot partitions (don't use timestamps as partition key)
✅ Prefer On-Demand mode for spiky workloads
✅ Enable Streams for change data capture
✅ Set TTL for expiring items automatically
✅ Use batch operations for large data imports
✅ Limit Scan operations — use Query where possible
✅ Enable auto-scaling if using provisioned mode

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🚫 16. Limitations

Limitation	Notes
No joins	Denormalized structure is ideal
Item size limit	Max 400 KB per item
Table size	Unlimited, but watch partition limits
Query flexibility	Limited compared to RDS

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🚀 17. Advanced Features

Feature	Description
PartiQL	SQL-like query language for DynamoDB
DAX (DynamoDB Accelerator)	In-memory caching for 10x performance boost
Global Tables	Multi-region replication and low-latency
Transaction API	ACID transactions for multiple items
Streams + Lambda	Event-driven data processing pipeline

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🧩 18. DynamoDB vs RDS vs Aurora

Feature	DynamoDB	RDS/Aurora
Type	NoSQL (Key-Value/Doc)	Relational SQL
Schema	Schema-less	Schema-defined
Joins	❌ No	✅ Yes
Scaling	Auto-scaling	Vertical + Read Replica
Latency	< 10ms	Higher
Use Case	High-scale, flexible	Structured, relational

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