SQL Complexity Checker

Q: What is a good complexity score?

A score of 0-30 is simple (straightforward, easy to maintain), 31-60 is moderate (acceptable for analytical workloads), and 61+ is complex (consider refactoring or adding indexes). Most production analytical queries fall in the 30-50 range.

Q: Does this tool execute my query?

No. The checker performs static analysis only. It parses SQL structure, counts patterns, and applies heuristic rules. Your SQL never leaves your browser.

Q: Which SQL dialects are supported?

The checker recognizes PostgreSQL, MySQL, BigQuery, Snowflake, and Redshift syntax patterns. It flags dialect-specific functions so you can assess portability.

Paste any SQL query to analyze its complexity. Detects nested subqueries, CTEs, window functions, joins, and custom dialects — with optimization tips for each dimension.

Paste your SQL query:

WITH regional_sales AS (
    SELECT
        r.region_name,
        DATE_TRUNC(''quarter'', o.order_date) AS quarter,
        SUM(oi.quantity * oi.unit_price) AS revenue,
        COUNT(DISTINCT o.customer_id) AS unique_customers
    FROM orders o
    INNER JOIN order_items oi ON o.id = oi.order_id
    INNER JOIN products p ON oi.product_id = p.id
    INNER JOIN customers c ON o.customer_id = c.id
    INNER JOIN regions r ON c.region_id = r.id
    WHERE o.status != ''cancelled''
    GROUP BY r.region_name, DATE_TRUNC(''quarter'', o.order_date)
),
ranked AS (
    SELECT *,
        RANK() OVER (PARTITION BY quarter ORDER BY revenue DESC) AS rank,
        LAG(revenue) OVER (PARTITION BY region_name ORDER BY quarter) AS prev_q_revenue
    FROM regional_sales
)
SELECT
    region_name,
    quarter,
    revenue,
    unique_customers,
    ROUND(revenue / NULLIF(unique_customers, 0), 2) AS arpu,
    rank,
    prev_q_revenue,
    ROUND(((revenue - prev_q_revenue) / NULLIF(prev_q_revenue, 0)) * 100, 1) AS qoq_growth_pct
FROM ranked
WHERE rank <= 5
ORDER BY quarter DESC, rank ASC;

How to Use

Paste Your SQL

Copy any SQL query — SELECT, INSERT, or complex analytical queries with CTEs and window functions.

Click Analyze

The checker scans for subqueries, CTEs, joins, window functions, aggregations, and dialect-specific features.

Get Optimization Tips

Receive a complexity score with actionable suggestions to simplify, optimize, or refactor your query.

What We Analyze

The SQL Complexity Checker evaluates queries across six dimensions:

Dimension	What It Measures	Why It Matters
Subquery Depth	Nested SELECTs and derived tables	Deep nesting hurts readability and optimizer performance
CTE Usage	WITH clauses and recursive CTEs	CTEs improve readability but can materialize unexpectedly
Join Complexity	Number and types of JOINs	Many joins increase execution time exponentially
Window Functions	RANK, LAG, ROW_NUMBER, etc.	Window functions add sorting overhead — check indexing
Aggregation Depth	GROUP BY with nested aggregates	Multi-level aggregation can hide performance pitfalls
Dialect Features	DATE_TRUNC, NULLIF, COALESCE, etc.	Vendor-specific functions limit portability

FAQ

What is a "good" complexity score?

A score of 0-30 is simple (straightforward, easy to maintain), 31-60 is moderate (acceptable for analytical workloads), and 61+ is complex (consider refactoring or adding indexes). Most production analytical queries fall in the 30-50 range.

Does this tool execute my query?

No. The checker performs static analysis only — it parses SQL structure, counts patterns, and applies heuristic rules. Your SQL never leaves your browser.

Which SQL dialects are supported?

The checker recognizes PostgreSQL, MySQL, BigQuery, Snowflake, and Redshift syntax patterns. It flags dialect-specific functions so you can assess portability.

Methodology and Disclosure

This SQL complexity checker is maintained by InfiniSynapse. Links to the InfiniSynapse app are first-party product links, and the score is a static heuristic based on visible SQL patterns.

The tool was last reviewed on June 11, 2026. It does not execute SQL, inspect indexes, or read database statistics, so use the result as a review aid rather than a substitute for an execution plan.

Ready for Agentic Analytics?

InfiniSynapse plans, executes, and verifies multi-step data analysis across PostgreSQL, MySQL, BigQuery, CSV files, and knowledge bases — with an AI agent that explains its reasoning at every step.

🚀 Try InfiniSynapse Free →