Free Amazon Redshift SQL Formatter & Beautifier Online

Amazon Redshift is a PostgreSQL-derived warehouse dialect with its own distribution, loading, and maintenance vocabulary. Analytical queries commonly use DATEADD and DATEDIFF, large window aggregations, and warehouse-sized GROUP BY clauses. Operational scripts can include COPY, UNLOAD, VACUUM, and encoding or sort-key definitions. Formatting needs to keep those warehouse concerns visible without making a reporting query look like ordinary transactional PostgreSQL.

This Redshift formatter lays out analytical projections, window frames, and aggregate filters in a stable order while preserving Redshift function calls and aliases. DATEADD intervals remain readable, HAVING stays attached to its aggregation, and statements such as COPY or UNLOAD can be reviewed alongside SELECT statements without losing their options. The result is useful for scheduled reports, Spectrum queries, data loads, and SQL embedded in transformation jobs.

The preset example uses date arithmetic, grouped event metrics, a rolling window, HAVING, and an explicit row limit. Start with it to see the intended layout, then paste a production query from the Redshift console or a pipeline repository. The editor is preset to Redshift for this URL, and the formatted-output diff helps you verify changes before sharing the cleaned query with your team.

The example keeps the relationship between a warehouse date window and its aggregate metrics easy to inspect.

The same structure helps reviewers spot warehouse-specific concerns such as broad date scans, expensive windows, and filters applied after aggregation. A consistent Redshift layout can be copied into a scheduled query, a dbt model, or a runbook without losing the distinction between analytical logic and operational statements.

Choose this page when the SQL is intended for Redshift rather than upstream PostgreSQL. Its sample and explanatory copy keep DATEADD, warehouse operations, and analytical windows in view so a reviewer can reason about the query in its actual execution environment.