Snowflake SQL Formatter
Free online Snowflake SQL formatter. Format Snowflake queries with support for VARIANT data types, FLATTEN, COPY INTO, QUALIFY clauses, and time travel syntax.
What is Snowflake?
Snowflake is a cloud-native data platform built for the modern data stack. Unlike traditional databases, Snowflake separates compute from storage, allowing teams to scale each independently and pay only for what they use. It runs on AWS, Azure, and Google Cloud, making it cloud-agnostic.
Snowflake is ANSI SQL compliant and extends standard SQL with semi-structured data types (VARIANT, OBJECT, ARRAY), time travel queries, data sharing, and native support for JSON, Avro, Parquet, and other formats. It is widely used for analytics, data engineering, and machine learning pipelines.
The Snowflake SQL formatter understands Snowflake-specific syntax including FLATTEN(), QUALIFY, COPY INTO, data path operators (data:city::string), and time travel clauses, producing consistently formatted queries for Snowflake workloads.
Frequently asked questions
Does the Snowflake formatter understand semi-structured data types?
Yes. Snowflake-specific syntax for VARIANT, OBJECT, and ARRAY types, along with path operators like data:city::string and FLATTEN(), are formatted correctly with appropriate spacing and line breaks.
Will COPY INTO and CREATE STAGE commands be formatted?
Yes. Snowflake DDL and DML including COPY INTO, CREATE STAGE, CREATE FILE FORMAT, MERGE, and CLONE statements are all supported and formatted with proper indentation.
Does it handle Snowflake time travel syntax?
Yes. Snowflake time travel syntax (e.g. AT(TIMESTAMP => ...) or BEFORE(STATEMENT => ...)) is preserved and formatted as part of FROM clause extensions.
Will QUALIFY clauses be formatted correctly?
Yes. Snowflake's QUALIFY clause (used to filter window function results) is formatted on its own line, similar to WHERE and HAVING, following Snowflake's SQL conventions.
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