A guide to the three most critical DynamoDB limits: item size, query/scan page size, and partition throughput, and how they impact data modeling.
Explains DynamoDB filter expressions, their limitations, and when to use them versus proper table design for efficient queries.
Explains how DynamoDB's design ensures scalable performance, contrasting it with the scaling challenges of relational databases.
Argues that the PIE theorem (Pattern Flexibility, Efficiency, Infinite Scale) is more practical for database selection than the popular CAP theorem.
Examines four common data modeling patterns for DynamoDB in serverless applications, including simple use cases and complex relational approaches.
