Data cardinality significantly affects indexing strategies in databases. Understanding how cardinality impacts indexing is crucial for optimizing database performance and query efficiency. By recognizing the cardinality of your data, you can choose the best indexing methods to ensure fast and reliable data retrieval.

Let us delve into the five vital ways how data cardinality affects indexing strategies. 

High cardinality and unique indexes

High cardinality columns, like user IDs or email addresses, benefit from unique indexes. Unique indexes ensure that each value in the column is distinct, improving search performance. They help quickly locate specific records, making them ideal for primary keys and unique constraints.

Low cardinality and bitmap indexes

Low cardinality columns, such as gender or boolean fields, are well-suited for bitmap indexes. Bitmap indexes are space-efficient and perform well with low-cardinality data. They use bitmaps to represent the presence of values, allowing for fast querying and filtering.

Composite indexes

When dealing with columns of varying cardinality, composite indexes can be effective. Composite indexes combine multiple columns into a single index. The order of columns in a composite index should consider cardinality, starting with the highest cardinality column to maximize efficiency.

Index selectivity

Cardinality influences index selectivity, which measures how well an index can narrow down search results. High cardinality columns provide high selectivity, making indexes more effective. Low cardinality columns offer lower selectivity, which can reduce index efficiency if not handled properly.

Index maintenance

Maintaining indexes on high cardinality columns can be resource-intensive. Updates, inserts, and deletes require index maintenance, which can impact performance. Understanding cardinality helps balance the benefits of indexing with the cost of maintenance, ensuring efficient database operations.

To sum up 

Data cardinality is a key factor in determining effective indexing strategies. Understanding how cardinality affects indexing enables you to design efficient databases that deliver fast and reliable query results.