Allocating too much memory to Postgres can actually slow down performance, especially during index builds. The author explains how exceeding certain memory thresholds can lead to inefficient data processing and increased write operations, which negatively impact speed. It's better to use modest memory settings and adjust only based on proven benefits.

The article discusses the advantages of indexing JSONB data types in PostgreSQL, emphasizing improved query performance and efficient data retrieval. It provides practical examples and techniques for creating indexes, as well as considerations for maintaining performance in applications that utilize JSONB fields.

Embracing a flexible approach to data storage, the article advocates for using PostgreSQL to store various types of data without overthinking their structure. It highlights the advantages of saving raw data in a database, allowing for easier modifications and queries over time, illustrated through examples like Java IDE indexing, Chinese character storage, and sensor data logging.

The article discusses the evolving strategies for scaling PostgreSQL databases, emphasizing the importance of understanding Postgres internals, effective data modeling, and the appropriate use of indexing. It also covers hardware considerations, configuration tuning, partitioning, and the potential benefits of managed database services, while warning against common pitfalls like over-optimization and neglected maintenance practices.