- PostgreSQL and MySQL require partition keys to be included in primary keys, leading to potential issues with uniqueness and query performance.
- Partition pruning, a key optimization, fails if the WHERE clause doesn't include the partition key, causing slow queries.
- Static partition boundaries can become imbalanced over time, creating operational overhead for manual rebalancing.
- Partitioning by the primary key (e.g., BIGINT AUTO_INCREMENT) ensures automatic pruning without code changes.
- Automated services can manage partitions by watching growth, splitting catch-all partitions, and handling retention, reducing manual work.
- Time-aligned boundaries can be derived from date columns without including them in the partition key, avoiding query leakage.
- Tools like pg_partman and TimescaleDB automate time-based partitioning but may leak keys into queries; a DIY service offers flexibility.
- Hash and list partitioning require monitoring for skew or promoting values from catch-all partitions, with automation focused on detection rather than splitting.
- Choosing a partition key that is already in all critical queries (like the primary key) prevents abstraction leaks and maintains performance.