The database index size estimator calculates approximate storage overhead for B-tree indexes based on row count, indexed column type, and index structure. Use this for storage capacity planning before adding indexes to large tables.
How to Estimate Database Index Size
Database indexes consume significant storage. A B-tree index stores key values, pointer data, and page overhead. For a 1M-row table with a BIGINT index, expect roughly 24-48 MB of index storage. Composite indexes multiply this by the number of indexed columns.
When to Add an Index
Add indexes on columns used frequently in WHERE clauses, JOINs, and ORDER BY for tables with 100K+ rows. The query speed gain typically justifies the storage cost and the small INSERT/UPDATE overhead. Monitor your actual index sizes with SHOW TABLE STATUS in MySQL or pg_indexes in PostgreSQL.
Frequently Asked Questions
Is this index size estimator free?
Yes, completely free with no signup required.
How accurate are the estimates?
Estimates are approximations based on typical B-tree overhead factors. Actual index sizes vary based on data distribution, fill factor settings, and database engine internals. Use these estimates for capacity planning, not exact provisioning.
What is B-tree index overhead?
B-tree indexes store sorted copies of indexed column values plus page pointers. Overhead includes: the key data itself, left/right child pointers (8 bytes each), and page-level overhead. PostgreSQL B-tree pages are 8KB; MySQL InnoDB pages are 16KB by default.
When should I add an index?
Add indexes on columns used frequently in WHERE clauses, JOIN conditions, and ORDER BY clauses for large tables (1M+ rows). Index overhead is justified when the query performance gain outweighs the storage cost and the slower INSERT/UPDATE speed from index maintenance.
What is a composite index?
A composite (multi-column) index covers multiple columns in a specific order. A composite index on (user_id, created_at) is used for queries filtering on user_id or filtering on both user_id AND created_at, but NOT for queries filtering on created_at alone.