PostgreSQL raises too_many_columns (error 54011) when a table, view, or subquery exceeds the 1600-column hard limit.
PostgreSQL Error 54011 – too_many_columns – appears when a CREATE TABLE, ALTER TABLE ADD COLUMN, or view definition tries to include more than 1600 columns. Redesign the schema by splitting the table, using wide-to-long pivot tables, or wrapping related fields in composite/JSONB types to stay under the limit.
PostgreSQL Error 54011
PostgreSQL throws error 54011 with condition name too_many_columns when a table, materialized view, temporary table, or subquery contains more than 1600 columns. The limit is hard-coded and applies to all major versions.
The check happens during CREATE TABLE, CREATE VIEW, SELECT * INTO, and any ALTER TABLE ADD COLUMN statement that would push the column count beyond 1600.
Fixing it requires redesigning the schema because the limit cannot be changed in configuration.
The primary trigger is a DDL or DML statement that produces a row type wider than 1600 attributes.
This often comes from denormalized “wide” tables, auto-generated ETL staging tables, or SELECT * pivots that enumerate hundreds of measure columns.
Conditional column generation in ORMs or migration scripts can silently add hundreds of nullable columns and hit the limit during deployment.
Because the cap is absolute, you must reduce the number of columns.
Split the wide table into logical groups linked by the primary key, move semi-structured data into JSONB, or model arrays/composite types for repeated attributes.
After schema changes, update queries, views, and application code to reference the new structures. Galaxy’s AI copilot can rewrite affected queries quickly inside the editor.
ETL staging tables generated from spreadsheets often exceed 1600 columns.
Load the file into a temporary JSONB staging table, then shred the JSONB into normalized tables.
Pivot queries that create a column per day or per metric should pivot data rows into key-value form instead. Use aggregate functions with FILTER or crosstab.
Normalize schemas early, avoid 1-to-1 spreadsheet migrations, and monitor column counts with catalog views like pg_class and pg_attribute.
Set CI checks to fail migrations that push a table near 1600 columns.
Galaxy Collections let teams audit endorsed schemas, reducing rogue migrations that add excessive columns.
Error 54000 (program_limit_exceeded) appears for row sizes that exceed the 1.6 GB tuple limit; fix by removing large columns. Error 54001 (statement_too_complex) appears when query plans exceed internal node limits; simplify the query or break it into parts.
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The absolute maximum is 1600 columns regardless of datatype. You cannot raise this limit via configuration.
Technically possible but strongly discouraged; many core assumptions break, and you would run an unsupported fork.
Yes. A physical DROP COLUMN reduces the live column count, but logically dropped columns still occupy attnum slots until VACUUM FULL or table rewrite.
Galaxy highlights schema diffs, warns when migrations push tables near 1600 columns, and its AI copilot suggests normalization tactics automatically.
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