single-table-design

This series of posts demonstrates efficient filtering and pagination with DynamoDB. Part 1: Duplicating data with Lambda and DynamoDB streams to support filtering Part 2: Using global secondary indexes and parallel queries to reduce storage footprint and write less code Part 3: How to make pagination work when the output of multiple queries have been combined Part 4: Storage and retrieval of comment statistics using index overloading and sparse indexes...

This series of posts demonstrates efficient filtering and pagination with DynamoDB. Part 1: Duplicating data with Lambda and DynamoDB streams to support filtering Part 2: Using global secondary indexes and parallel queries to reduce storage footprint and write less code Part 3: How to make pagination work when the output of multiple queries have been combined Part 4: Storage and retrieval of comment statistics using index overloading and sparse indexes...

This series of posts demonstrates efficient filtering and pagination with DynamoDB. Part 1: Duplicating data with Lambda and DynamoDB streams to support filtering Part 2: Using global secondary indexes and parallel queries to reduce storage footprint and write less code Part 3: How to make pagination work when the output of multiple queries have been combined Part 4: Storage and retrieval of comment statistics using index overloading and sparse indexes...

It never ceases to amaze me just how much is possible through the seemingly constrained model that DynamoDB gives us. It’s a fun puzzle to try to support access patterns beyond a simple key value lookup, or the retrieval of an ordered set of items. The NoSQL gods teach us to store data in a way that mirrors our application’s functionality. This is often achieved by duplicating data so that it appears in multiple predefined sets for inexpensive retrieval....