PostgreSQL performance problems often look like application problems first. An API gets slow, Kafka lag grows, report generation stalls, or a background job starts timing out. The database may be involved, but the root cause is usually a boundary between query shape, indexing, data volume, and application behavior.
This hub organizes Bytz Echo articles around PostgreSQL as a production system, not just a database tutorial topic.
Performance investigations
- API Slow? Database Fine ? Real Performance Case Study – a reminder that database blame can be premature.
- JPA vs JDBC Performance ? 10M Rows (PostgreSQL) – what changes when data volume makes abstraction cost visible.
- Kafka Lag vs PostgreSQL Writes: What Slowed the Consumer Down – when consumer throughput depends on database write behavior.
Spring Boot and PostgreSQL integration
- Spring Boot CRUD Operations Guide with PostgreSQL – baseline CRUD patterns for Spring Boot applications.
- Call Stored Procedures in PostgreSQL with Spring Boot 3 – stored procedure integration when logic moves closer to data.
- Create Stored Procedures and Functions in PostgreSQL – PostgreSQL-side function and procedure design basics.
Infrastructure and background work
- How to Set Up PostgreSQL Database Server with Docker – local infrastructure for database experiments.
- JobRunr with Spring Boot: In-Memory Jobs vs Database Persistence – background job persistence trade-offs.
- Spring Boot Quartz Scheduler Guide with Examples – scheduled work and persistence considerations.
Suggested next articles
- Why PostgreSQL Query Performance Dropped After Adding an Index
- The Reporting Query That Blocked Production Writes
- Spring Boot Connection Pool Tuning for PostgreSQL Under Load