PostgreSQL Query Catalog

Find all CHECK constraints (except NOT NULL) of domains that are not associated with any column.

Find all CHECK constraints (except NOT NULL) that are associated with a base table or a foreign table column. It is useful to enforce as many constraints at database level as possible. In this way one improves data quality as well as gives extra information to the database users (including the DBMS engines, development environments, and applications).

Make sure that Boolean expressions take into account precedence rules of Boolean operators. AND operator has precedence over OR operator.

Find regular expressions where a predefined character class is incorrectly specified, e.g. [digit] instead of [:digit:].

Find base tables and foreign tables where based on a check constraint, a key constraint, and a NOT NULL constraint can be at most one row. Make sure that this is the real intent behind the constraint, not a mistake. Find tables where a check constraint permits only one possible value in a column, the column has NOT NULL constraint, and constitutes a key, i.e., has the PRIMARY KEY or UNIQUE constraint.

This query identifies all expressions that use the non-standard length() function. Although length() is a functional synonym for char_length() in PostgreSQL, its use is discouraged for two primary reasons: char_length() is the SQL-standard function, and length() has different semantics in other database systems (e.g., returning byte length in MySQL). To enhance code portability and prevent semantic ambiguity for developers, this query flags all instances of length() to encourage standardization on the char_length() function.

This query identifies base table columns that, based on their name, are presumed to store personal names but lack an explicit maximum length constraint. It operates on a heuristic, flagging columns with names like first_name, surname, etc., that are defined with unbounded textual types (e.g., text, varchar) and have no corresponding CHECK constraint to limit their length (e.g., char_length(col) <= n). The absence of such a limit is a design flaw that can introduce usability issues in front-end applications and create potential security vulnerabilities related to excessive data submission.

Find non-foreign key base table columns that name refers to the possibility that these are used to register e-mail addresses. Find the columns that do not have any simple CHECK constraint that contains @ sign. A simple check constraint covers a single column. In this case registration of e-mail addresses without @ is most probably not prohibited.

This query identifies non-foreign key columns with a textual data type that lack essential validation. It specifically targets columns that are missing both of the following fundamental checks:

• A constraint to prohibit the insertion of empty or whitespace-only strings.
  
• A constraint to enforce a character set or format policy (e.g., via a regular expression).
  

Find non-foreign key base table columns that name refers to the possibility that these are used to register prices/quantities. Find the columns that do not have any simple CHECK constraints, i.e., a constraint that covers only this column. In this case registration of negative price/quantity is most probably not prohibited.

Find base tables columns with temporal types (date and timestamp) that do not belong to a foreign key and that do not have any associated simple CHECK constraints, i.e., constraint that involves only one column. For instance, in the column registration_time that does not have any associated CHECK constraints could be values '1200-01-01 00:00' or '5900-12-31 00:00'. Rows with these values most probably represent wrong propositions and the system should restrict registration of such data.

Find non-foreign key base table columns that name refers to the possibility that these are used to register URLs. Find the columns that do not have any simple CHECK constraint that references to a protocol. A simple check constraint covers a single column. In this case registration of URLs without a protocol is most probably not prohibited.

This query identifies non-foreign key columns of base tables with a textual data type that lack any simple (single-column) CHECK constraint. The absence of such constraints indicates a complete lack of column-level validation, creating a risk of low-quality data ingress, including the implicit allowance of empty or whitespace-only strings.

Identify possibly missing CHECK constraints.

What are the base tables and foreign tables without any associated (directly or through domains) check constraints? A NOT NULL constraint is a kind of CHECK constraint. However, this query does not take into account NOT NULL constraints.

Find base table and foreign table columns with the Boolean type that has a CHECK constraint that involves only this column. Avoid unnecessary CHECK constraints. The Boolean type contains only two values and there is nothing to check. By creating a check that determines that possible values in the column are TRUE and FALSE, one duplicates the attribute constraint (column has a type). This is a form of duplication.

Find CHECK constraints on base table or foreign table columns that contain data about e-mail addresses and apply unnecessary restrictions to the these, rejecting potentially some legal addresses. More precisely, find CHECK constraints that prevent registration of e-mail addresses with multiple @ signs.

Write correct constraints. Usually the constraint expression should refer to at least one column. A domain constraint expression should refer to the stub VALUE. For instance, the constraint CHECK(1=0) that is associated with a table T would prevent adding any rows to T. The value of the Boolean expression of this constraint is always FALSE.

This query identifies a logical contradiction between data validation rules and default value definitions. It flags CHECK constraints involving two columns where both columns share the same DEFAULT value, yet the constraint enforces a strict inequality (e.g., col1 < col2) or non-equality (col1 <> col2). This configuration is logically flawed because attempting to insert a row using the default values for both columns will result in an immediate constraint violation (as X < X evaluates to false). This renders the default values mutually exclusive and unusable in practice.

Find check constraints that involve columns with the type Boolean.