Database Index Analyzer

The analyzer parses your CREATE TABLE statements to build a schema map (columns + existing indexes), then inspects each SELECT query's WHERE filters, JOIN ON conditions, and ORDER BY columns. Any column referenced in these clauses that has no matching single-column or composite index is flagged as missing.

A redundant index is one whose columns are a leading prefix of another index. For example, if you have INDEX (status) and INDEX (status, created_at), the first index is redundant — any query that could use INDEX (status) alone can also use the composite index. Redundant indexes waste disk space and slow down INSERT/UPDATE/DELETE without providing any query benefit.

Use a composite index when your queries consistently filter on multiple columns from the same table together. The database can use a composite index (a, b) for queries filtering on 'a' alone, 'a AND b', or 'a' with ORDER BY b — but not for 'b' alone. Put equality columns first, then range/sort columns. Multiple single-column indexes are better when columns are used independently in different queries.

Without an index on the foreign key column, JOIN operations cause a full table scan of the joined table for each row in the driving table. With an index, each join lookup is O(log n) instead of O(n). For tables with thousands of rows, this is the single most common cause of slow JOIN queries.

No. All analysis runs entirely in your browser using JavaScript. Your schema and query text never leave your machine.

The analyzer supports standard SQL syntax compatible with MySQL, PostgreSQL, and SQLite. It handles CREATE TABLE with INDEX/KEY definitions inline, PRIMARY KEY constraints, and standard SELECT with WHERE, JOIN ON, and ORDER BY clauses. PostgreSQL-style SERIAL/BIGSERIAL columns and MySQL-style backtick quoting are both handled.