DynamoDB with Clojure

DynamoDB is operationally powerful, but only when key design, capacity mode, access patterns, and stream behavior are part of the application design. This chapter keeps those decisions visible while showing where Clojure data transformations belong around AWS client calls.

Read the child lessons as a sequence of design decisions. The goal is not to memorize every database feature, but to learn where Clojure’s data-first style makes database code easier to test, inspect, and operate.

In this section

• Overview of AWS DynamoDB
  Use Overview of AWS DynamoDB to connect NoSQL data modeling, query behavior, and Clojure boundary code so Java engineers can make storage decisions that remain testable and operationally explicit.
  • DynamoDB Data Model: A Comprehensive Guide for Java and Clojure Developers
    Explore the intricacies of AWS DynamoDB's data model, including tables, items, attributes, and primary keys, and learn how to leverage its schemaless nature for flexible data solutions.
  • DynamoDB Benefits: Scalability, Cost Efficiency, and AWS Integration
    Explore the benefits of using AWS DynamoDB, including scalability, cost efficiency, and seamless integration with AWS services, for building robust and scalable applications.
• Provision DynamoDB Tables and Capacity
  Plan DynamoDB table keys, capacity modes, and throughput expectations before Clojure services depend on them.
  • Creating Tables with Provisioned and On-Demand Capacity Modes in DynamoDB
    Explore the intricacies of creating DynamoDB tables with provisioned and on-demand capacity modes, including step-by-step instructions and best practices for Java and Clojure developers.
  • Managing Read and Write Capacity Units (RCUs and WCUs) in DynamoDB
    Learn how to effectively manage Read and Write Capacity Units (RCUs and WCUs) in AWS DynamoDB to optimize performance and cost.
• Accessing DynamoDB from Clojure Using Amazonica
  Use Accessing DynamoDB from Clojure Using Amazonica to connect NoSQL data modeling, query behavior, and Clojure boundary code so Java engineers can make storage decisions that remain testable and operationally explicit.
  • Amazonica Library: Simplifying AWS Integrations with Clojure
    Explore the Amazonica library, a powerful AWS SDK wrapper for Clojure, designed to simplify AWS service integrations with idiomatic functions. Learn how to add Amazonica to your project using Leiningen and leverage its capabilities for seamless cloud interactions.
  • AWS Credentials and Client Configuration for Clojure
    Learn how to configure AWS credentials and clients in Clojure using Amazonica, with a focus on security best practices and practical code examples.
• DynamoDB CRUD and Batch Operations
  Map Clojure data operations to DynamoDB item reads, writes, updates, deletes, and batch workflows.
  • Creating and Updating Items in DynamoDB with Clojure
    Master the art of creating and updating items in DynamoDB using Clojure. Learn to use put-item and update-item operations effectively, with condition expressions to manage data integrity.
  • Reading Items in DynamoDB with Clojure: Mastering Data Retrieval
    Explore advanced techniques for reading items from AWS DynamoDB using Clojure, including get-item operations, querying with partition keys, and optimizing data retrieval with filters and projections.
  • Deleting Items in DynamoDB with Clojure: Ensuring Safe and Consistent Data Management
    Explore the intricacies of deleting items in DynamoDB using Clojure, focusing on condition expressions, consistency models, and best practices to prevent accidental data loss.
  • Batch Operations in DynamoDB with Clojure: Enhancing Performance and Throughput
    Explore batch operations in AWS DynamoDB using Clojure. Learn about batch-write-item and batch-get-item, handling unprocessed items, and optimizing performance.
• Leveraging DynamoDB Streams for Real-Time Applications
  Use Leveraging DynamoDB Streams for Real-Time Applications to connect NoSQL data modeling, query behavior, and Clojure boundary code so Java engineers can make storage decisions that remain testable and operationally explicit.
  • Understanding DynamoDB Streams: Real-Time Data Processing for Scalable Applications
    Explore the intricacies of DynamoDB Streams, their architecture, use cases, and integration with Clojure for real-time data processing and synchronization.
  • AWS Lambda Stream Processing with Clojure: Integrating DynamoDB Streams
    Learn how to set up AWS Lambda functions to process DynamoDB Streams using Clojure, including deployment strategies and event handling.
• Case Study: Scaling an E-Commerce Backend
  Use Case Study: Scaling an E-Commerce Backend to connect NoSQL data modeling, query behavior, and Clojure boundary code so Java engineers can make storage decisions that remain testable and operationally explicit.
  • Designing the Data Model for Products and Orders in E-Commerce with DynamoDB
    Explore the intricacies of designing a scalable data model for e-commerce systems using DynamoDB, focusing on products and orders. Learn about entity modeling, primary keys, indexes, and handling complex relationships.
  • Implementing Shopping Cart Functionality in Clojure with DynamoDB
    Learn how to design and implement a scalable shopping cart functionality using Clojure and DynamoDB, focusing on atomic updates, session management, and handling anonymous users.
  • Handling High Traffic and Scaling: Strategies for Clojure and NoSQL
    Explore strategies for managing high traffic and scaling NoSQL databases with Clojure, including capacity monitoring, auto-scaling, and optimizing data access patterns.