Snowflake SQL Query Formatter & Beautifier

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Format Snowflake Data Cloud SQL queries including LATERAL FLATTEN, VARIANT semi-structured paths (v:attr::string), and QUALIFY clauses.

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SQL Dialects:Standard SQL PostgreSQL (JSONB)Google BigQuery Oracle PL/SQL Snowflake SQL

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Input SQL Query

Ctrl+Enter to format619 chars

with flattened_events as (select e.event_id, e.ingested_at::timestamp_ntz as event_ts, e.payload:customer:account_id::string as account_id, f.value:sku::string as item_sku, f.value:qty::number(10,0) * f.value:unit_price::float as line_revenue from raw_telemetry.public.checkout_stream e, lateral flatten(input => e.payload:line_items) f where e.ingested_at >= dateadd('day', -7, current_timestamp())) select account_id, item_sku, sum(line_revenue) as total_gmv, count(distinct event_id) as order_count from flattened_events group by 1, 2 qualify row_number() over (partition by account_id order by total_gmv desc) <= 5;

Formatted SQL Result

WITH
  flattened_events AS (
    SELECT
      e.event_id,
      e.ingested_at::timestamp_ntz AS event_ts,
      e.payload:customer:account_id::string AS account_id,
      f.value:sku::string AS item_sku,
      f.value:qty::number(10, 0) * f.value:unit_price::float AS line_revenue
    FROM
      raw_telemetry.public.checkout_stream e,
      LATERAL flatten(input => e.payload:line_items) f
    WHERE
      e.ingested_at >= dateadd('day', -7, current_timestamp())
  )
SELECT
  account_id,
  item_sku,
  sum(line_revenue) AS total_gmv,
  count(DISTINCT event_id) AS order_count
FROM
  flattened_events
GROUP BY
  1,
  2
QUALIFY
  row_number() over (
    PARTITION BY
      account_id
    ORDER BY
      total_gmv desc
  ) <= 5;

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How do I use Snowflake SQL Query Formatter & Beautifier?

Paste your Snowflake SQL query or dbt model into the left editor (or inspect the pre-loaded `LATERAL FLATTEN` + `VARIANT` sample).

Confirm that Dialect is pre-set to 'Snowflake SQL' with 2-space indentation.

Review the formatted Snowflake query with aligned `LATERAL FLATTEN(INPUT => ...)`, `::` casts, and `QUALIFY` window filters.

Click 'Copy' to paste the clean query into Snowsight, DBeaver, Hex, or your dbt project.

What features does Snowflake SQL Query Formatter & Beautifier offer?

Pre-configured for the Snowflake Data Cloud dialect (`snowflake` parser)

Supports Snowflake `VARIANT`, `OBJECT`, and `ARRAY` semi-structured traversal (`raw_event:cart.items`)

Preserves `LATERAL FLATTEN(INPUT => ...)` named argument syntax (`=>`) and `::` type casting

Formats `QUALIFY`, `IFF()`, `PARSE_JSON()`, `DATEADD()`, and `COPY INTO` warehouse statements

Pre-loaded with a Snowflake semi-structured event flattening query ready to test

100% Client-Side execution: warehouse table names and Snowpipe definitions stay in your browser

Snowflake Semi-Structured `VARIANT` & `LATERAL FLATTEN` Syntax Reference

Snowflake combines colon (`:`) path extraction with double-colon (`::`) type casting and `=>` named parameters—all of which are preserved by our Snowflake dialect engine.

Snowflake SQL Constructs Supported by the Formatter
Snowflake Feature	Syntax Pattern	Warehouse Use Case	Why Standard Formatters Break It
VARIANT Path + Cast	raw_event:user_id::string	Extracting typed fields from JSON/Parquet	Confuses : path with :: cast
LATERAL FLATTEN	LATERAL FLATTEN(INPUT => arr)	Expanding nested JSON arrays into rows	Breaks => named parameter arrow
QUALIFY Clause	QUALIFY ROW_NUMBER() OVER (...) = 1	Filtering window functions without CTEs	Fails to recognize QUALIFY keyword
Time Travel	AT(OFFSET => -60*5) / BEFORE(...)	Querying historical table snapshots	Misformats AT/BEFORE clauses

How is Snowflake SQL Query Formatter & Beautifier used in real-world workflows?

Snowflake Data & Analytics Engineers

Formatting `LATERAL FLATTEN` Pipelines over Semi-Structured JSON

Clean up staging models that ingest raw Kafka, Segment, or S3 Parquet `VARIANT` columns and flatten them into relational dimensional tables.

BI & Looker / Tableau Developers

Simplifying Window Deduplication Queries with `QUALIFY`

Format analytical queries that use Snowflake's `QUALIFY` clause to deduplicate CDC streams without wrapping queries in extra outer CTEs.

Data Platform Administrators

Standardizing `COPY INTO`, `CREATE STAGE`, and `TASK` DDL Scripts

Beautify Snowflake infrastructure-as-code SQL scripts before code review.

Frequently Asked Questions about Snowflake SQL Query Formatter & Beautifier

Why must I cast Snowflake `VARIANT` values with `::string` or `::number`?

Extracting a field from a `VARIANT` column using `payload:field_name` returns another `VARIANT` value (which still includes JSON quotes for strings). Casting with `payload:field_name::string` (or `::number`) extracts the native SQL scalar type and enables proper join and filter performance.

Does this formatter support `LATERAL FLATTEN(INPUT => ...)`?

Yes! The `snowflake` dialect engine recognizes Snowflake's `=>` named argument operator and `LATERAL FLATTEN` table function syntax without corrupting the arrow operator.

Can I format dbt Jinja SQL templates here?

Standard SQL blocks around `{{ ref('...') }}` format cleanly; for heavy Jinja macros (`{% for %}`), we recommend formatting the compiled SQL from `target/compiled/` or formatting the core `SELECT` body.

Are my Snowflake queries transmitted to any external server?

No. All formatting runs 100% locally in your browser's JavaScript runtime.

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