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5 PostgreSQL performance bottlenecks every DBA should know in 2026

Rajni Baliyan | July 7, 2026

FATAL: remaining connection slots are reserved for non-replication superuser connections

As applications become increasingly distributed, it's common for hundreds, or even thousands, of services to open database connections simultaneously. Because PostgreSQL creates a dedicated operating system process for every connection, exhausted connection pools can quickly bring an application to a halt.

• Applications suddenly unable to connect
• Traffic spikes overwhelming available connections
• Large numbers of idle sessions

• Deploy a connection pooler such as PgBouncer
• Tune application connection pools
• Configure session timeout settings to remove idle connections automatically

Slow queries begin timing out despite healthy hardware.

PostgreSQL never immediately removes rows after UPDATE or DELETE operations. Instead, "dead tuples" accumulate until they're cleaned up by VACUUM. When autovacuum can't keep up, indexes grow, tables become bloated, and query performance steadily degrades.

Organizations with heavy transactional workloads, such as financial services or ecommerce platforms, are especially vulnerable.

• Gradually increasing query latency
• Statement timeout errors
• Tables growing much faster than expected

• Tune autovacuum for high-write tables
• Monitor table and index bloat regularly
• Periodically rebuild heavily fragmented tables during maintenance windows

ERROR: could not write to temporary file: No space left on device

Large sorts, hash joins, or reporting queries often exceed available memory. When that happens, PostgreSQL writes temporary files to disk.

One poorly optimized query can consume tens, or even hundreds, of gigabytes of temporary storage, filling disks in minutes.

The good news? Once the offending query stops, PostgreSQL automatically removes the temporary files.

• Sudden disk usage spikes
• Reporting jobs failing unexpectedly
• Temporary storage reaching critical capacity

• Tune work_mem appropriately
• Configure temp_file_limit
• Store temporary files on dedicated storage when possible

ERROR: canceling statement due to conflict with recovery

Read replicas are often used to offload reporting and analytics from production databases. But long-running queries on standby servers can delay replication, causing stale data or forcing PostgreSQL to cancel user queries.

As replication lag grows, business reports become outdated and fail to reflect current production data.

• Growing replication lag
• Frequent recovery conflict errors
• Reports returning stale information

• Balance reporting workloads across multiple replicas
• Configure standby timeout settings appropriately
• Use Hot Standby Feedback where appropriate while monitoring primary table bloat

ERROR: could not write to file "pg_wal/...": No space left on device

One of the easiest production issues to overlook is an abandoned replication slot.

Replication slots guarantee that PostgreSQL retains Write-Ahead Log (WAL) files until replicas have consumed them. If a replica is decommissioned without removing its replication slot, WAL files continue accumulating indefinitely until disk space is exhausted.

This issue can silently develop over weeks before suddenly bringing production to a stop.

• Rapidly growing pg_wal directories
• Inactive replication slots
• Disk capacity alerts

• Monitor replication slot activity
• Configure WAL retention limits
• Include replication slot cleanup in infrastructure decommissioning procedures