SQL Index Helper
Analyze SQL queries to suggest optimal indexes for WHERE, JOIN, ORDER BY, and GROUP BY — with MySQL, PostgreSQL, and MariaDB support
Paste one or more SQL statements. The tool analyzes WHERE, JOIN, ORDER BY, and GROUP BY clauses to suggest indexes.
Override dialect detection or leave on auto-detect for automatic syntax analysis.
What is the SQL Index Helper?
The SQL Index Helper analyzes your SQL queries and recommends which indexes to create for optimal performance. It examines WHERE, JOIN, ORDER BY, and GROUP BY clauses to identify columns that would benefit from indexing, suggests composite indexes when multiple columns appear together, and generates ready-to-use CREATE INDEX statements tailored to your database engine (MySQL, PostgreSQL, or MariaDB).
How to Use
- Paste one or more SQL statements into the input area
- Optionally select your database engine (or leave on auto-detect)
- Review suggested single-column and composite indexes
- Copy the generated CREATE INDEX statements directly into your database
- Use EXPLAIN to validate improvements on your actual data
Use Cases
- Query optimization — Identify missing indexes causing full table scans
- Schema review — Audit existing queries for index coverage gaps
- Migration planning — Generate index DDL when moving to a new database
- Composite index design — Get column ordering right (equality before range before sort)
- Cross-dialect support — Generate dialect-aware DDL with proper quoting and tips
Example: Composite Index Suggestion
Given this query:
SELECT u.name, u.email
FROM users u
WHERE u.status = 'active'
AND u.created_at > '2024-01-01'
ORDER BY u.created_at DESC;
The tool suggests a composite index on (status, created_at) because
status is an equality filter (placed first for optimal leftmost-prefix usage)
and created_at is both a range filter and sort column (placed second to
enable index-ordered reads without an extra sort step).
Column Ordering in Composite Indexes
The tool applies database engine best practices for column ordering:
- Equality columns first — Columns compared with
=narrow the search space most effectively - Range columns second — Columns with
>,<,BETWEENuse the index partially - Sort columns last — Columns in ORDER BY benefit from index-ordered reads
Dialect Detection
The tool auto-detects your SQL dialect from syntax cues: backtick quoting and AUTO_INCREMENT indicate MySQL, SERIAL/RETURNING/ILIKE indicate PostgreSQL, and MariaDB-specific comments indicate MariaDB. Generated CREATE INDEX statements use appropriate quoting and include dialect tips (CONCURRENTLY for PostgreSQL, ALGORITHM=INPLACE for MySQL/MariaDB).
Privacy and Security
All analysis happens entirely in your browser using JavaScript. Your SQL queries — which may contain table names, column names, and business logic — never leave your device. No data is stored, logged, or transmitted to any server.
Frequently Asked Questions
What SQL clauses does the SQL Index Helper analyze?
The tool analyzes four types of clauses: WHERE (to identify filter columns that benefit from indexes), JOIN ON (to identify join key columns), ORDER BY (to identify columns used for sorting), and GROUP BY (to identify columns used for aggregation grouping). Each clause type generates specific index recommendations.
What is a composite index and when is it suggested?
A composite (multi-column) index covers multiple columns in a single index structure. The tool suggests composite indexes when multiple columns from the same table appear in WHERE clauses together, or when WHERE filter columns combine with ORDER BY or GROUP BY columns. Column order in a composite index matters — equality columns come first, followed by range columns, then sort columns.
How does the tool differentiate between MySQL, PostgreSQL, and MariaDB?
The tool detects dialect from syntax cues in your SQL: backtick quoting and AUTO_INCREMENT indicate MySQL, SERIAL/RETURNING/ILIKE/:: indicate PostgreSQL, and MariaDB-specific comments indicate MariaDB. The generated CREATE INDEX statements use appropriate identifier quoting (backticks for MySQL/MariaDB, double quotes for PostgreSQL) and include dialect-specific tips like CONCURRENTLY for PostgreSQL or ALGORITHM=INPLACE for MySQL.
Why does column order matter in a composite index?
Database engines use composite indexes left-to-right. A query can only use the index if it filters on the leftmost columns first. The tool places equality columns (=) before range columns (>, <, BETWEEN) because equality conditions narrow the search space more effectively. Sort columns come last to enable index-ordered reads without an additional sort operation.
Will the suggested indexes always improve performance?
Not necessarily. Index suggestions are candidates based on query structure analysis. Actual performance depends on data distribution, table size, write frequency, and existing indexes. Over-indexing can slow INSERT/UPDATE operations. Use EXPLAIN or EXPLAIN ANALYZE on your specific queries to validate whether a suggested index provides measurable improvement.
Is my SQL sent to any server for analysis?
No. All analysis runs entirely in your browser using JavaScript. Your SQL queries — which may contain table names, column names, and business logic — never leave your device. No data is stored, logged, or transmitted to any server.
Can I paste multiple SQL queries at once?
Yes. The tool splits your input by semicolons (respecting string literals and comments) and analyzes each statement independently. Index suggestions are aggregated across all statements, and duplicate suggestions for the same column are consolidated.
What is the difference between SQL Index Helper and SQL Query Analyzer?
The SQL Query Analyzer detects anti-patterns (SELECT *, missing WHERE, cartesian products) and estimates query complexity. The SQL Index Helper focuses specifically on recommending which indexes to create based on column usage in WHERE, JOIN, ORDER BY, and GROUP BY clauses. Use both together: first identify structural issues with the analyzer, then optimize with index suggestions from this tool.