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AWS Services - DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. Unlike SQL databases, DynamoDB does not use tables with joins and complex schemas but instead focuses on key-value and document data models.

Key Features

  • NoSQL Database: Key-value and document-based.
  • Fully Managed: No server provisioning, patching, or scaling required.
  • Performance: Single-digit millisecond latency.
  • Scalability: Auto-scaling with on-demand capacity.
  • Availability: Multi-AZ replication by default.
  • Security: Encryption at rest and in transit, IAM-based access control.
  • Integration: Works seamlessly with AWS Lambda, Streams, API Gateway, S3, etc.

Core Concepts

Tables

  • A collection of data in DynamoDB.
  • Each table must have a primary key defined.

Items

  • Equivalent to a row in SQL.
  • Each item is a set of attributes (key-value pairs).

Attributes

  • Equivalent to columns in SQL.
  • DynamoDB allows flexible attributes — items in the same table may have different attributes.

Primary Key

Two options:

  1. Partition Key (simple primary key)
    • A single attribute used to uniquely identify each item.
    • Example: UserId.
  2. Partition Key + Sort Key (composite primary key)
    • Uniqueness is determined by the combination of partition and sort key.
    • Example: UserId (partition key) + OrderDate (sort key).

Secondary Indexes

  • Allow querying data with alternative keys.

  • Global Secondary Index (GSI)

    • Partition + sort key can be different from the base table.
  • Local Secondary Index (LSI)
    • Uses the same partition key as the base table but a different sort key.

Provisioned vs On-Demand Capacity

  • Provisioned: You define Read Capacity Units (RCUs) and Write Capacity Units (WCUs).
  • On-Demand: Pay per request; DynamoDB auto-scales.

Storage and Performance

  • Data is stored across multiple partitions automatically.
  • Performance is tied to partition keys:
    • Hot partition problem occurs if one key is accessed disproportionately.
    • Use good partition key design to distribute load.
  • DynamoDB Accelerator (DAX): In-memory caching layer for microsecond response times.

Common Features

Streams

  • Capture item-level changes (insert, update, delete).
  • Commonly used with AWS Lambda for event-driven architectures.

Time to Live (TTL)

  • Automatically deletes expired items based on a timestamp attribute.

Encryption

  • Default: AWS-managed KMS key.
  • Option: Use customer-managed CMKs.

Transactions

  • ACID transactions across multiple items and tables.

Backups

  • On-demand backups: Full backups.
  • Point-in-time recovery (PITR): Continuous backup with restore to any second in the last 35 days.

AWS Console Options for DynamoDB

  1. Tables

    • Create and manage tables.
    • Define partition and sort keys.
    • Configure capacity (on-demand or provisioned).
    • Enable Streams, TTL, encryption.

  2. Items

    • Insert, edit, delete items directly.
    • Run queries and scans.

  3. Indexes

    • Create and monitor GSIs and LSIs.

  4. Backups and Restore

    • Manage PITR and on-demand backups.
    • Restore a backup into a new table.

  5. Metrics & Monitoring

    • CloudWatch metrics: throttled reads/writes, consumed capacity.
    • DynamoDB console dashboards.

  6. Global Tables

    • Multi-region replication for disaster recovery and low-latency global access.

Example CLI Commands

Create a new table:

aws dynamodb create-table
--table-name Users
--attribute-definitions AttributeName=UserId,AttributeType=S
--key-schema AttributeName=UserId,KeyType=HASH
--billing-mode PAY_PER_REQUEST

Insert an item:

aws dynamodb put-item
--table-name Users
--item '{"UserId": {"S": "123"}, "Name": {"S": "Alice"}}'

Query items:

aws dynamodb query
--table-name Users
--key-condition-expression "UserId = :id"
--expression-attribute-values '{":id":{"S":"123"}}'

Best Practices

  • Design tables based on access patterns, not just data storage.
  • Use composite keys to allow flexible queries.
  • Avoid hot partitions by distributing partition keys evenly.
  • Use DAX for read-heavy workloads.
  • Enable PITR backups for resilience.
  • Use Streams + Lambda for serverless event processing.

DynamoDB Use Cases

  • Gaming leaderboards.
  • Session management.
  • IoT device data storage.
  • Shopping carts.
  • Event logging and analytics.