Best practices for modeling data with secondary indexes

Concluding this chapter with data modeling best practices for secondary indexes is a great way to round out the discussion. These practices delve into how to effectively structure your data to optimize performance and meet your application’s access patterns. Let us dive into them now.

Designing sparse indexes

We know by now that secondary indexes can be used to model the same data in an alternate view with a different key schema compared to the base table. This alternate key schema is based purely on the access patterns that the application needs to support.

One common type of access pattern revolves around finding a needle in a haystack – retrieving a tiny subset of items with a certain filter from a large dataset. Scanning the whole table to retrieve this tiny subset of items is highly inefficient, as most of the items do not qualify for this access pattern, yet you are paying for reading through them...