🗃️Amazon DynamoDB

NEW

Also known as: DynamoDB

A fully managed NoSQL key-value and document database with single-digit millisecond latency at scale.

DESCRIPTION

Amazon DynamoDB is a serverless NoSQL database that provides consistent single-digit millisecond response times at virtually any scale. It supports key-value and document data models with automatic scaling, multi-Region replication, and built-in security. Features include streams for change data capture, TTL, transactions, and flexible indexing via local and global secondary indexes. Capacity can be provisioned or on-demand, and integration with Lambda and other AWS services enables event-driven architectures. It is well-suited for high-traffic applications like gaming, IoT, retail carts, and session stores.

ALTERNATIVE DEFINITIONS

AWS

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale.

Highlights serverless nature and high-performance focus.

Source

AWS Documentation

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.

Emphasizes performance predictability and scalability.

Source

RELATED TERMS

NoSQL Key-Value Store Shard Key Global Secondary Index On-Demand Capacity Provisioned Capacity DynamoDB Streams Global Tables AWS Lambda Serverless

COMPETING TERMS

MongoDB Apache Cassandra Google Cloud Bigtable Azure Cosmos DB

RELATIONS

• Broader: Key-Value Store NoSQL

KNOWLEDGE AREAS

Cloud Data Services Data Storage & Operations Data Engineering Real-time & Streaming Data

TARGET AUDIENCE

Data Engineer Software Developer Cloud Architect DevOps Engineer Solution Architect

EXTERNAL SOURCES

• Wikipedia - Amazon DynamoDB
• AWS - Official DynamoDB developer guide
• AWS - Product overview and features
• AWS Well-Architected - Best practices for DynamoDB workloads

TOP QUESTIONS

What workloads fit Amazon DynamoDB best?

High-throughput, low-latency access patterns with well-defined keys such as shopping carts, sessions, user profiles, and IoT telemetry are ideal.

Category: UseCase

How does DynamoDB achieve scalability?

It partitions data by partition key, automatically redistributing and scaling capacity across partitions as throughput and storage grow.

Category: Architecture

What is a common modeling mistake in DynamoDB?

Using relational modeling patterns without considering access patterns leads to hot partitions and inefficient queries. Start from access patterns.

Category: Mistakes

How do Global Secondary Indexes help?

GSIs provide alternate query access patterns by projecting attributes and using new partition/sort keys, enabling flexible lookups.

Category: Technique

What are DynamoDB Streams used for?

They capture item-level changes for event-driven processing, replication, auditing, or materialized views with consumers like AWS Lambda.

Category: Integration

When to choose on-demand vs provisioned capacity?

On-demand fits unpredictable traffic. Provisioned is cost-effective for stable workloads and supports auto scaling and reserved capacity.

Category: Decision

How does DynamoDB handle transactions?

It supports ACID transactions across multiple items and tables with TransactWriteItems and TransactGetItems APIs.

Category: Feature

What are the security features of DynamoDB?

Integration with IAM, encryption at rest and in transit, VPC endpoints, and fine-grained access control via condition keys.

Category: Security

What are competitors to DynamoDB?

MongoDB, Apache Cassandra, Azure Cosmos DB, and Google Cloud Bigtable are major alternatives for similar workloads.

Category: Alternatives