Configured hibernate.jdbc.batch_size (e.g., 20) along with statement ordering.

: Many developers encounter the "N+1 query problem" or locking issues that cause applications to crawl. The "story" of high performance often involves moving away from default settings and understanding the underlying database mechanics. The Narrative Arc : The book typically follows a path from JDBC basics Hibernate optimization , and finally to database-specific tuning (like PostgreSQL or SQL Server). Technical "Chapters" (The 20-Page Perspective)

Caching reduces read latency by keeping frequently accessed, static data close to the application layer.

is the definitive guide by Vlad Mihalcea for mastering data access performance in enterprise applications. Originally published in 2016 and updated through 2020 and 2024 editions , the book bridges the gap between Java developers and Database Administrators (DBAs) by focusing on how frameworks like Hibernate and JPA interact with relational databases. Core Concepts of High-Performance Persistence

The GenerationType.IDENTITY strategy forces Hibernate to execute an immediate SQL INSERT statement to find out the database-assigned ID. This completely breaks write-batching mechanisms.

If you were looking for the "story" behind this book or a narrative about Java persistence performance, here is the context: The Story of the Book The Author's Mission

High-performance persistence starts with a mindset shift. Java applications should not treat the database as a dumb storage engine. Modern relational database management systems (RDBMS) like PostgreSQL, Oracle, and MySQL are highly optimized computational engines.