sql formatter with comments: Examples, How It Works, Best Practices

When teams search for a sql formatter with comments, they need a tool that keeps code clean without stripping hard-earned context. Comments are living documentation for business rules, test notes, and optimizer hints — yet manual formatting is slow, inconsistent, and error-prone. A good formatter preserves inline and block comments, aligns them with the right clauses, and keeps queries readable for review and production. AI2sql accelerates this end-to-end: from a plain-English prompt or a rough SQL draft, you get a clean, dialect-aware query that preserves or generates helpful comments on request. The dominant intent here is informational and solution-seeking, mapped to a Product/Feature utility (SQL formatter). Key takeaway: AI2sql is the fastest path from question to correct, commented SQL — for beginners who want clarity and for pros who need production-ready readability.

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What is sql formatter with comments?

A sql formatter with comments is a tool that standardizes casing, indentation, and clause layout while preserving inline comments (--) and block comments (/* ... */). It ensures notes, TODOs, query owners, and optimizer hints remain intact and aligned with the relevant SQL tokens. The result is cleaner diffs in Git, faster code reviews, and fewer misunderstandings across BI, analytics, and engineering teams.

• Preserves inline (--) and block (/* ... */) comments.

• Normalizes indentation and clause breaks (SELECT, FROM, JOIN, WHERE, GROUP BY, ORDER BY).

• Optionally inserts helpful comments (e.g., intent, risk areas) when requested.

• Understands dialect specifics so comments and hints are not lost.

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How sql formatter with comments Works with AI2sql

Inputs

• Plain English: Describe your metric, filters, or tables (e.g., 'Weekly active users excluding test domains').

• Schema context: Share table and column names or connect a database for introspection.

• Formatting guidance: Ask to keep, insert, or reorganize comments (e.g., 'add comments before each join').

Outputs

• SQL: Clean, validated query that preserves or generates comments.

• Explanation: Plain-language summary of what the query does and why clauses are placed as they are.

• Variations: Alternative versions by dialect (MySQL, Postgres, Snowflake, BigQuery) or by performance trade-offs.

AI2sql also supports end-to-end workflows across engines. For example, see the AI2sql PostgreSQL integration for dialect-aware generation and formatting.

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Real sql formatter with comments Examples (copy-paste)

Postgres: Finance team formatting a monthly revenue report while preserving analyst comments.

/* Report: Monthly revenue by product; owner: finance_analytics */ WITH orders AS (   SELECT o.order_id, o.order_date::date AS order_date, o.product_id, o.total_amount   FROM sales_orders o   -- Only paid orders considered; refunds handled downstream   WHERE o.status = 'PAID' AND o.order_date >= current_date - interval '90 days' ) SELECT date_trunc('month', order_date) AS month,        p.category,        sum(o.total_amount) AS revenue FROM orders o JOIN dim_products p ON p.product_id = o.product_id GROUP BY 1, 2 ORDER BY month DESC, p.category;

Example: sql formatter with comments for MySQL reporting query.

/* Dashboard: weekly active users */ SELECT /*+ SET_VAR(sort_buffer_size = 8388608) */  -- Preserve optimizer hint        DATE_FORMAT(a.activity_date, '%Y-%u') AS iso_week,        COUNT(DISTINCT a.user_id) AS wau FROM user_activity a -- Exclude internal test accounts LEFT JOIN users u ON u.id = a.user_id WHERE a.activity_date >= DATE_SUB(CURDATE(), INTERVAL 12 WEEK)   AND (u.email NOT LIKE '%@example.test' OR u.email IS NULL) GROUP BY iso_week ORDER BY iso_week DESC;

BigQuery: Marketing cohort query with block and inline comments.

/* Cohort performance: New vs returning users */ WITH sessions AS (   SELECT     user_id,     DATE(session_start) AS session_date   FROM app_sessions   -- Only web events for the past 60 days   WHERE platform = 'web' AND session_start >= DATE_SUB(CURRENT_DATE(), INTERVAL 60 DAY) ) SELECT   DATE_TRUNC(session_date, WEEK(MONDAY)) AS week_start,   COUNT(DISTINCT user_id) AS active_users FROM sessions GROUP BY week_start ORDER BY week_start DESC;

Snowflake: Operations capacity planning with preserved TODO note.

/* TODO: validate capacity threshold with ops */ WITH daily AS (   SELECT     CAST(event_time AS DATE) AS d,     COUNT_IF(event_type = 'JOB_STARTED') AS jobs_started,     COUNT_IF(event_type = 'JOB_FAILED') AS jobs_failed   FROM events   WHERE event_time >= DATEADD(day, -30, CURRENT_DATE())   GROUP BY d ) SELECT   d,   jobs_started,   jobs_failed,   CASE WHEN jobs_failed > 0 THEN 'ATTENTION' ELSE 'OK' END AS status -- Simple status label FROM daily ORDER BY d DESC;

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Best Practices and Limitations

• Place intent comments at the start of each clause or CTE so they survive edits and refactors.

• Use short, factual comments that explain why, not what (the SQL already shows what).

• Retain optimizer hints in dialects that support them; avoid moving hint comments away from the SELECT token.

• Watch for tools or pipelines that strip comments; verify downstream compatibility before relying on comments for lineage.

• Do not put secrets or PII in comments; treat comments as production-visible metadata.

Limitations: Some ETL/BI exporters remove comments; dialect rules vary for hints; extremely long comments can hurt readability and line wrapping. AI2sql keeps comments intact while optimizing layout for review and version control.

Generate SQL for sql formatter with comments instantly with AI2sql - no technical expertise required.

Try sql formatter with comments with AI2sql

Getting started is simple: open the builder, describe your question in plain English, optionally paste a rough SQL draft, and specify if you want comments preserved or added. AI2sql returns a clean, commented query along with a human-readable explanation and dialect-specific variants when needed. You can then copy-paste to your warehouse or continue iterating. Explore more engines, including our PostgreSQL integration, and generate equally clean SQL for MySQL, Snowflake, and BigQuery. To learn about the broader workflow, visit the AI2sql platform.

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Conclusion

A reliable sql formatter with comments preserves knowledge while making queries easier to read, share, and review. Instead of hand-tuning indentation or risking lost context, use AI2sql to go from a natural-language request to an accurate, commented SQL query in minutes. Whether you need Postgres, MySQL, BigQuery, or Snowflake, AI2sql produces clean, readable results and helps your team standardize style without losing intent. Ready to move faster from idea to production-ready SQL?

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