Critique of the Active Record pattern, explaining its inefficiencies in data access and performance issues in applications and APIs.
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.
A tutorial on using Mongoose's Population feature to link MongoDB collections, preventing document size limits by separating blog posts and comments.
Discusses common pitfalls and challenges when using non-relational databases, focusing on difficulties in changing primary keys and access patterns.
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.
A guide to optimizing costs when using Azure Cosmos DB, covering its pricing model, design considerations, and best practices for efficient usage.
Demonstrates how to model and query graph-like data in MongoDB using the Aggregation Framework's graph lookup, inspired by a scenario from 'Designing Data-Intensive Applications'.
Discusses the pros and cons of soft deletion vs. hard deletion in databases, with a focus on Django implementations and related libraries.
A guide for developers on common database mistakes beginners make, including storing images, using limit/offset for pagination, and relying on integer primary keys.
A guest post in a series exploring methods and best practices for tracking document versions within MongoDB databases.
A rebuttal to a critical blog post about Spring Data MongoDB, defending its design and clarifying misconceptions about its ORM-like features.
Explains how to implement user-defined ordering in RavenDB, moving from a complex MSSQL approach to a simpler document-based solution.
Explains how to use the Array datatype in PostgreSQL for storing and querying data like tags or purchase items, with practical examples.
