DynamoDB Basics Interview Questions

Master Amazon DynamoDB fundamentals with interview-focused questions and answers covering architecture, tables, items, partition keys, sort keys, CRUD operations, consistency, DAX, Global Tables, TTL, backups, and production best practices.

Introduction

Amazon DynamoDB is a fully managed, serverless NoSQL database service provided by AWS. It is designed to deliver single-digit millisecond latency at virtually any scale while automatically handling infrastructure management, replication, scaling, backups, and fault tolerance.

Many of the world's largest applications use DynamoDB because it provides:

Unlimited Scalability
High Availability
Low Latency
Fully Managed Infrastructure
Serverless Operations

Companies including Amazon, Netflix, Airbnb, Lyft, Samsung, Capital One, Disney+, Snap, and Roblox use DynamoDB for mission-critical workloads.

This guide covers the most frequently asked DynamoDB interview questions for Java Developers, Cloud Engineers, Backend Engineers, DevOps Engineers, and Solution Architects.

DynamoDB Architecture

flowchart LR

Application --> API --> DynamoDB

DynamoDB --> Partitions

Partitions --> SSDStorage

DynamoDB --> Replication

Replication --> MultipleAZs

1. What is Amazon DynamoDB?

Answer

Amazon DynamoDB is a

Fully Managed
Serverless
NoSQL
Key-Value
Document Database

that provides

Automatic Scaling
High Availability
Low Latency
Multi-AZ Replication

without requiring infrastructure management.

2. Why was DynamoDB created?

Traditional databases required

Server Management
Manual Scaling
Capacity Planning
Replication Configuration
Backup Management

DynamoDB eliminates these operational tasks by providing a managed database service.

3. What type of database is DynamoDB?

DynamoDB is

NoSQL Database
Key-Value Database
Document Database
Fully Managed Cloud Database

4. What are the key features of DynamoDB?

Serverless
Fully Managed
Automatic Scaling
Multi-AZ Replication
Low Latency
High Availability
On-Demand Capacity
Global Tables
Encryption at Rest
Point-in-Time Recovery

5. What are common DynamoDB use cases?

User Profiles
Shopping Carts
Session Management
Banking Applications
Gaming Leaderboards
IoT Applications
Event Logging
Recommendation Systems

6. DynamoDB vs Relational Database?

DynamoDB	RDBMS
NoSQL	Relational
Serverless	Self Managed
Automatic Scaling	Manual Scaling
Schema Flexible	Fixed Schema
No JOINs	JOIN Supported
Millisecond Latency	Depends on Workload

7. DynamoDB vs Cassandra?

DynamoDB	Cassandra
Fully Managed	Self Managed
AWS Service	Open Source
Serverless	Cluster Management
Automatic Scaling	Manual Scaling
Global Tables	Multi-DC Replication

8. What is Serverless?

Serverless means

AWS manages

Servers
Scaling
Backups
Replication
Maintenance

Developers focus only on application development.

9. What is a Table?

A Table stores related items.

Example

Customer

Order

Employee

10. What is an Item?

An Item represents a single record.

Equivalent to

Row

in relational databases.

Example

{
  "CustomerId":"1001",
  "Name":"Venugopal",
  "City":"San Antonio"
}

11. What is an Attribute?

Attributes are fields inside an item.

Example

CustomerId

Name

City

Salary

12. What is a Primary Key?

Every DynamoDB table requires a primary key.

Types

Partition Key
Composite Primary Key

13. What is a Partition Key?

Partition Key determines

Data Distribution
Physical Partition
Storage Location

Example

CustomerId

Partition Flow

flowchart LR

CustomerId --> HashFunction --> Partition --> StorageNode

14. What is a Sort Key?

Sort Key determines ordering within a partition.

Example

OrderDate

15. What is a Composite Primary Key?

Combination of

Partition Key

+

Sort Key

Example

CustomerId

+

OrderDate

16. Explain DynamoDB Data Types.

Scalar

String
Number
Binary
Boolean
Null

Document

List
Map

Set

String Set
Number Set
Binary Set

17. Does DynamoDB support nested JSON?

Yes.

Example

{
  "Address": {
      "City":"San Antonio",
      "State":"Texas"
  }
}

18. CRUD Operations

Create

PutItem

Read

GetItem

Update

UpdateItem

Delete

DeleteItem

19. Difference between Query and Scan?

Query	Scan
Uses Key	Reads Entire Table
Fast	Slow
Low Cost	Expensive
Production Ready	Avoid When Possible

20. What is Conditional Write?

Writes succeed only if a condition is true.

Example

attribute_not_exists(CustomerId)

Useful for preventing duplicate records.

21. What are Batch Operations?

Supported APIs

BatchGetItem
BatchWriteItem

Benefits

Reduced Network Calls
Better Performance

22. What is TTL?

TTL

Time To Live

Automatically deletes expired items.

Example

Session Data

Expires after

24 Hours

23. What is Point-in-Time Recovery (PITR)?

Allows restoring a table to any second within the retention window.

Benefits

Recover Deleted Data
Recover Corrupted Data
Disaster Recovery

24. How are backups handled?

Supported

On-Demand Backup
Automated Backup
PITR

25. What are Global Tables?

Global Tables replicate data across AWS Regions.

Benefits

Multi-Region Applications
Low Latency
Disaster Recovery

Global Tables

flowchart LR

US-East

<--> Europe

Europe

<--> Asia

26. What is DynamoDB Accelerator (DAX)?

DAX is an in-memory cache for DynamoDB.

Benefits

Microsecond Reads
Lower Read Latency
Reduced DynamoDB Read Requests

27. Does DynamoDB encrypt data?

Yes.

Supports

AWS KMS
Encryption at Rest
Encryption in Transit

28. What consistency models does DynamoDB support?

Eventually Consistent Reads
Strongly Consistent Reads

Eventually Consistent is the default.

29. What are common limitations?

No JOINs
No Stored Procedures
Limited Aggregations
Query-Based Design
Hot Partition Risk

30. Real Production Example

A banking application stores customer transactions.

Primary Key

CustomerId

Sort Key

TransactionTime

Benefits

Fast Customer History
Millisecond Reads
Automatic Scaling
Multi-Region Replication

DynamoDB Request Flow

flowchart LR

Application --> PartitionKey --> HashFunction --> Partition --> Replication --> Response

Enterprise Best Practices

Design tables around access patterns.
Choose high-cardinality partition keys.
Prefer Query over Scan.
Enable Auto Scaling.
Enable Point-in-Time Recovery.
Enable Encryption using AWS KMS.
Use TTL for temporary data.
Use DAX for read-heavy workloads.
Monitor CloudWatch metrics.
Avoid hot partitions.

Quick Revision

Topic	Key Point
Database	NoSQL
Type	Key-Value + Document
Management	Fully Managed
Scaling	Automatic
Storage	Serverless
Primary Key	Partition or Composite
Read API	GetItem
Write API	PutItem
Query	Fast
Scan	Slow
Cache	DAX
Backup	PITR
Multi-Region	Global Tables
Encryption	AWS KMS

Interview Tips

Interviewers commonly ask

Why DynamoDB over RDS?
Explain serverless databases.
Query vs Scan.
What is DAX?
What are Global Tables?
Explain TTL.
Explain PITR.
Difference between Partition Key and Sort Key.
When should DynamoDB be used?
What causes hot partitions?

Always answer with production use cases and discuss the trade-offs between scalability, consistency, and cost.

Summary

Amazon DynamoDB is a fully managed, serverless NoSQL database designed for applications requiring massive scalability, low latency, and high availability. Features such as automatic scaling, Global Tables, DAX, Point-in-Time Recovery, and built-in encryption make it an excellent choice for cloud-native applications.

Understanding DynamoDB fundamentals—including tables, items, attributes, primary keys, CRUD operations, Query vs Scan, TTL, Global Tables, DAX, and backups—provides the foundation for advanced topics such as partition key design, indexing, transactions, streams, and performance optimization covered in the following chapters.