Database Performance Anti-Patterns - Design Choices We Learned the Hard Way
Wednesday, October 21 at 13:35–14:25
Modern application development has changed how databases are designed and used. Teams move faster, systems grow more complex, and database decisions are increasingly made by developers without dedicated database specialists. In this environment, performance issues often emerge not from scale itself, but from common design choices that don’t behave well under real workloads.
This presentation explores database performance anti-patterns - recurring query and schema design decisions that consistently lead to inefficiencies in production systems. Using PostgreSQL as the primary example, the talk examines how these patterns affect I/O, memory usage, indexing, query planning, and partitioning behavior.
Topics include data access patterns such as SELECT *, query constructs that prevent index usage, pitfalls of NOT IN, schema-level choices such as storing timestamps as strings or numbers, using 4-byte integers for auto-generated primary keys, and defining all columns as nullable - decisions that often seem harmless but create long-term performance and maintenance costs.
While the examples focus on PostgreSQL, the concepts apply broadly to relational databases. The goal is to help developers better understand how design decisions impact database performance and avoid patterns that have repeatedly caused problems for users.
