• Workshop: Advanced Design Patterns for Amazon DynamoDB
    • Start here: Setup
      • Step 1 - Open the AWS Systems Manager Console
      • Step 2 - Check the Python and AWS CLI installation
      • Step 3 - Check boto3 installation
      • Step 4 - Check the content of the workshop folder
      • Step 5 - Check the files format and content
      • Step 6 - Preload the items for the table Scan exercise
    • Exercise 1: DynamoDB Capacity Units and Partitioning
      • Step 1 - Create the DynamoDB table
      • Step 2 - Load sample data into the table
      • Step 3 - Load a larger file to compare the execution times
      • Step 4 - View the CloudWatch metrics on your table
      • Step 5 - Increase the capacity of the table
      • Step 6 - After increasing the table’s capacity, load more data
      • Step 7 - Create a new table with a low-capacity global secondary index
    • Exercise 2: Sequential and Parallel Table Scans
      • Step 1 - Execute a sequential Scan
      • Step 2 - Execute a parallel Scan
    • Exercise 3: Global Secondary Index Write Sharding
      • Step 1 - Creating the GSI
      • Step 2 - Querying the GSI with shards
    • Exercise 4: Global Secondary Index Key Overloading
      • Step 1 - Create the employees table for global secondary index key overloading
      • Step 2 - Load data into the new table
      • Step 3 - Query the employees table using the global secondary index with overloaded attributes
    • Exercise 5: Sparse Global Secondary Indexes
      • Step 1 - Add a new global secondary index to the employees table
      • Step 2 - Scan the employees table to find managers without using the sparse global secondary index
      • Step 3 - Scan the employees table to find managers by using the sparse global secondary index
    • Exercise 6: Composite Keys
      • Step 1 - Create a new global secondary index for City-Department
      • Step 2 - Query all the employees from a state
      • Step 3 - Query all the employees of a city
      • Step 4 - Querying all the employees of a city and a specific department
    • Exercise 7: Adjacency Lists
      • Step 1 - Create and load the the InvoiceandBilling table
      • Step 2 - Review the InvoiceAndBills table on the DynamoDB console
      • Step 3 - Query the table's invoice details
      • Step 4 - Query the Customer details and Bill details using the Index
    • Exercise 8: Amazon DynamoDB Streams and AWS Lambda
      • Step 1 - Create the replica table
      • Step 2 - Review the AWS IAM policy for the IAM role
      • Step 3 - Create the Lambda function
      • Step 4 - Enable DynamoDB Streams
      • Step 5 - Map the source stream to the Lambda function
      • Step 6 - Populate the logfile table and verify replication to logfile_replica
  • Scenarios: Design Challenges
    • Retail Cart Scenario
      • Retail Cart References
    • Bank Payments Scenario
      • Bank Payments References
  • Links: NoSQL Design: Reference Materials

  •   Contributing (GitHub)
  •  Authors

  • Clear History
Privacy | Site terms | © 2020 Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Edit this page
Amazon DynamoDB Labs > NoSQL Design: Reference Materials

NoSQL Design: Reference Materials

DynamoDB Design: Reference Materials

DynamoDB Data Model Design:

  • Working with Queries in DynamoDB
  • Advanced Design Patterns for DynamoDB
  • DynamoDB Best Practices for Designing and Architecting with DynamoDB
  • Best Practices for Using Sort Keys to Organize Data
  • Using Global Secondary Indexes in DynamoDB
  • Best Practices for Managing Many-to-Many Relationships

Understanding Distributed Systems and DynamoDB:

  • Amazon DynamoDB Under the Hood: How We Built a Hyper-Scale Database
  • Amazon DynamoDB: How It Works

DynamoDB Related Tools:

  • NoSQL Workbench for Amazon DynamoDB
  • EMR-DynamoDB-Connector: Access data stored in Amazon DynamoDB with Apache Hadoop, Apache Hive, and Apache Spark

Online Training Courses:

  • Linux Academy: Amazon DynamoDB Deep Dive
  • edX: Amazon DynamoDB: Building NoSQL Database-Driven Applications