PostgreSQL raises error 53000 (insufficient_resources) when the server cannot allocate the memory, disk, or connection slots needed to run the current statement.
PostgreSQL Error 53000 – insufficient_resources – means the server lacks memory, disk space, or free connections to run your query. Free resources (increase work_mem, add disk, or raise max_connections) and rerun the statement to resolve the error.
PostgreSQL Error 53000
PostgreSQL returns error code 53000 with the condition name insufficient_resources when it cannot obtain the memory, disk space, temporary file capacity, or connection slots required to execute a query, create an index, or open a new session.
The backend aborts the statement immediately because continuing could compromise server stability or data integrity.
Fixing the error fast is critical because lack of resources can cascade into more failures and user downtime.
Running a sort, hash join, or CTE that exceeds work_mem or temp_file_limit forces PostgreSQL to request more memory or spill to temporary files. If neither is available, the planner stops with insufficient_resources.
Shared memory, WAL disk exhaustion, or reaching max_connections also trigger the same error class.
In containerized or cloud deployments, tight RAM or disk quotas frequently surface this problem.
First, identify the exhausted resource in the server log: memory context, disk path, or connection count. Then raise the relevant parameter or clean space. Most fixes require a postgresql.conf change and reload, not a full restart.
Typical remedies include increasing work_mem for large sorts, raising temp_file_limit, enlarging the tablespace disk volume, or bumping max_connections when session slots are exhausted.
Always monitor after applying the change.
Bulk data loads with COPY often fill the WAL directory. Move pg_wal to a larger disk or enable archive_mode to prevent overflow.
Complex analytics queries spill huge temp files. Move temp_tablespaces to a faster, larger volume or rewrite the query to stream less data.
Set realistic work_mem based on available RAM minus shared_buffers.
Use statement_timeout to abort rogue queries before they absorb all resources.
Implement connection pooling with PgBouncer to keep max_connections low. Regularly vacuum and monitor disk usage with pg_stat_disk across all tablespaces.
Error 53100 disk_full surfaces when a write cannot complete due to lack of space. Error 53300 too_many_connections appears when connection slots are exhausted. Both share similar root causes and fixes.
Error 53200 out_of_memory arises when the allocator cannot fulfill a memory request.
Solutions overlap: tune work_mem and shared_buffers or add RAM.
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Large sorts or hash joins need more memory than work_mem, and no temp space is free, causing the backend to abort.
temp_file_limit or disk capacity under pgsql_tmp is exceeded during query execution.
WAL or data directory runs out of space during inserts, COPY, or autovacuum, stopping further writes.
The server has no free backend slots, and connection requests fail with insufficient resources.
OS-level cgroups or cloud instance limits prevent PostgreSQL from allocating additional memory.
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Only when the error is triggered by memory intensive operations. If disk or connections are exhausted, increasing work_mem will not help.
Yes. Many parameters like work_mem and temp_file_limit can be changed in-session or with a reload. Disk and WAL moves require brief downtime.
Check the PostgreSQL server log. The line before the error usually states memory context, file path, or connection limit that failed.
Galaxy surfaces query execution plans, memory usage hints, and endorses optimized SQL, reducing the likelihood of runaway queries that exhaust resources.
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