The blog post delves into the intricacies of choosing between Local Secondary Indexes (LSIs) and Global Secondary Indexes (GSIs) in Amazon DynamoDB, highlighting their distinct functionalities and appropriate use cases. LSIs are tied closely to the base table's partition, sharing throughput and allowing strongly consistent reads, but they impose limitations on data size and throughput and require careful planning due to their constraints. In contrast, GSIs offer greater flexibility by supporting different partition keys and providing additional throughput capacity, though they only support eventually consistent reads and can lead to non-monotonic read results. The author emphasizes the importance of understanding each index type's implications, particularly for cost and scalability, and hints at future discussions around secondary index projection choices and the pitfalls of a trend known as "overloading" GSIs. The article is part of a broader series aimed at clarifying DynamoDB data modeling concepts, moving beyond misconceptions related to single table design.