What is cardinality in Databases?

A source of confusion may be the use of the word in two different contexts - data modelling and database query optimization.

In data modelling terms, cardinality is how one table relates to another.

• 1-1 (one row in table A relates to one row in tableB)
• 1-Many (one row in table A relates to many rows in tableB)
• Many-Many (Many rows in table A relate to many rows in tableB)

There are also optional participation conditions to the above (where a row in one table doesn't have to relate to the other table at all).

See Wikipedia on Cardinality (data modelling).

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When talking about database query optimization, cardinality refers to the data in a column of a table, specifically how many unique values are in it. This statistic helps with planning queries and optimizing the execution plans.

See Wikipedia on Cardinality (SQL statements).

It depends a bit on context. Cardinality means the number of something but it gets used in a variety of contexts.

• When you're building a data model, cardinality often refers to the number of rows in table A that relate to table B. That is, are there 1 row in B for every row in A (1:1), are there N rows in B for every row in A (1:N), are there M rows in B for every N rows in A (N:M), etc.
• When you are looking at things like whether it would be more efficient to use a b*-tree index or a bitmap index or how selective a predicate is, cardinality refers to the number of distinct values in a particular column. If you have a PERSON table, for example, GENDER is likely to be a very low cardinality column (there are probably only two values in GENDER) while PERSON_ID is likely to be a very high cardinality column (every row will have a different value).
• When you are looking at query plans, cardinality refers to the number of rows that are expected to be returned from a particular operation.

There are probably other situations where people talk about cardinality using a different context and mean something else.