DynamoDB Basics: NoSQL Databases and Use Cases

Lesson Objectives

By the end of this lesson, you will:

1. Understand what Amazon DynamoDB is and how it differs from relational databases.
2. Learn the key features and benefits of DynamoDB as a NoSQL database.
3. Explore common use cases for DynamoDB.
4. Create a DynamoDB table and perform basic operations.

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Introduction: A New Era of Databases

Relational databases have been the gold standard for structured data, but as applications grow more complex, the need for highly scalable, low-latency solutions has emerged. NoSQL databases like Amazon DynamoDB address these challenges by offering flexible schemas and distributed architectures.

In this chapter, we’ll dive into the basics of DynamoDB, AWS’s fully managed NoSQL database, and explore how it empowers developers to build fast, scalable applications.

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What is Amazon DynamoDB?

Amazon DynamoDB is a fully managed NoSQL database service that delivers fast and predictable performance with seamless scalability. Unlike relational databases, it stores data in a flexible, key-value, or document model, making it ideal for applications with diverse or evolving data structures.

Key Features:

1. Managed Service: DynamoDB handles infrastructure, scaling, and backups.
2. Low Latency: Millisecond response times for applications at any scale.
3. Flexible Schema: No rigid table structure—adapt to changes without downtime.
4. Global Reach: Supports multi-Region replication for global applications.
5. Integrated Security: Works with IAM, encryption, and fine-grained access controls.

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Key Concepts in DynamoDB

1. Tables

• A table is a collection of items, similar to a table in a relational database.

2. Items

• An item is a single row in a table. Each item is identified by a unique primary key.

3. Attributes

• Attributes are the individual data elements of an item, similar to columns in a table.

4. Primary Key

• Partition Key: A single attribute used to distribute data.
• Partition Key + Sort Key: A composite key for finer data access.

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How DynamoDB Differs from Relational Databases

Feature	DynamoDB	Relational Database
Schema	Flexible	Fixed
Data Model	Key-Value, Document	Tabular
Scaling	Automatic, Horizontal	Manual, Vertical
Joins	Not Supported	Supported
Consistency	Eventually Consistent (Default)	Strong Consistency (Default)

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Common Use Cases for DynamoDB

1. E-Commerce Applications:
   • Store product catalogs and user session data with low latency.
   • Example: Amazon’s shopping cart system.
2. Real-Time Analytics:
   • Manage sensor data from IoT devices.
   • Example: Temperature and humidity readings in smart homes.
3. Gaming Applications:
   • Track player profiles, game states, and leaderboards.
   • Example: Real-time multiplayer match history.
4. Mobile Backends:
   • Store user preferences and app settings.
   • Example: A personalized news feed for social media.

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Step-by-Step Lab: Creating a DynamoDB Table

Scenario: Build a DynamoDB table to store customer information for an e-commerce application.

Step 1: Create a DynamoDB Table

1. Log in to AWS:
   • Open the AWS Management Console and search for DynamoDB.
2. Create a Table:
   • Click Create Table.
   • Configure the table:
     • Table Name: Customers.
     • Partition Key: CustomerID (String).
     • Leave other settings as default for this lab.
3. Provisioned or On-Demand Capacity:
   • Select On-Demand Capacity (ideal for unpredictable workloads).
4. Create Table:
   • Click Create Table and wait for the table to initialize.

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Step 2: Insert Data into the Table

1. Add Items:
   • Navigate to the Items tab and click Create Item.
   • Enter JSON data:
     

     
     {
     “CustomerID”: “C001”,
     “Name”: “John Doe”,
     “Email”: “john.doe@example.com”,
     “Orders”: 5
     }
     

   • Save the item.
2. Add Another Item:
   • Create another item with CustomerID: C002 and different attributes.

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Step 3: Query the Table

1. Perform a Query:
   • Go to the Explore Table tab.
   • Specify CustomerID as the partition key and enter C001.
   • Click Run to view the matching item.
2. Scan the Table:
   • Use the Scan option to retrieve all items from the table.

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Step 4: Set Up a Global Secondary Index (Optional)

1. Add an Index:
   • Navigate to the Indexes tab and click Create Index.
   • Set Email as the index key to allow queries by email address.
2. Query Using the Index:
   • Use the new index to find items by email addresses.

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Reflection: Why Choose DynamoDB?

1. Scalability: Handles massive workloads automatically.
2. Flexibility: Adapts to changing data models without schema changes.
3. Performance: Delivers low-latency responses for real-time applications.

In this lab, you:

1. Created a DynamoDB table to store structured data.
2. Inserted, queried, and scanned data programmatically.
3. Explored how DynamoDB can power modern, scalable applications.

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What’s Next?

In the next module, we’ll focus on Monitoring and Cost Optimization, starting with AWS CloudWatch to monitor DynamoDB and other resources effectively.

Your database expertise is growing—let’s keep building!