Database Technology

The enable_seqscan GUC does not strictly prevent sequential scans; it merely lowers their cost weight to discourage the planner from choosing them. Developers often mistakenly believe setting this to off will force index usage, but the planner may still select a sequential scan if it is the only viable execution path. This behavior is by design, as full table scans are sometimes the only way to satisfy a query.

• enable_seqscan only influences planner cost estimates, it does not enforce index-only scans
• Setting off will not prevent sequential scans when no other execution plan exists
• Relying on this GUC to force index usage is a common misconception that leads to performance issues
• Use EXPLAIN ANALYZE to verify actual execution plans rather than assuming GUCs dictate behavior

A PostgreSQL 14 instance is generating an error message that the software version cannot logically produce. This indicates a mismatch between the binary code and the error catalog or internal state. The anomaly suggests potential corruption or a build artifact issue rather than standard query behavior.

• Verify the exact binary build and patch level against the error definition.
• Check for corrupted system catalogs or shared memory state.
• Reproduce in a non-production environment to isolate the trigger.
• Consider binary replacement if build artifacts are suspect.

An examination of governance challenges in financial services reveals that while individual teams like data engineering and AI development make sound, responsible decisions in isolation, significant risks emerge when viewing their interactions holistically. The C.A.L.M. platform test is introduced to identify these cross-functional misalignments, specifically where data movement for AI experimentation creates visibility gaps between engineering, AI, and compliance groups. This approach highlights how decentralized mandates can inadvertently lead to governance blind spots despite local adherence to best practices.

• Siloed team decisions often mask cross-functional governance risks in AI data pipelines.
• The C.A.L.M. framework exposes misalignments between data engineering and AI teams.
• Compliance visibility gaps arise when data moves to isolated experimental environments.
• Holistic reviews are necessary to catch issues invisible in individual team conversations.

Amazon RDS for PostgreSQL 18 introduces key logical replication enhancements, including default parallel streaming and automatic replication slot cleanup via idle_replication_slot_timeout. Users can now publish stored generated columns, toggle two-phase commit on active subscriptions, and monitor conflicts using new pg_stat_subscription_stats counters. These features are available for RDS for PostgreSQL 18.0+ and Aurora PostgreSQL.

• Parallel streaming is enabled by default, likely improving replication throughput for large datasets.
• Use idle_replication_slot_timeout to automatically clean up unused replication slots and prevent disk exhaustion.
• Monitor subscription health with new conflict counters in pg_stat_subscription_stats for faster troubleshooting.
• Publish stored generated columns using the new publish_generated_columns parameter for complex schemas.
• Toggle two-phase commit on running subscriptions without restarting them, reducing operational downtime.

Fleet impact: For RDS PostgreSQL and Aurora fleets, enable idle_replication_slot_timeout immediately to prevent storage bloat from orphaned slots. Review pg_stat_subscription_stats to detect replication lag or conflicts early, and verify parallel streaming is active to optimize WAN-bound replication performance.