gitbook/products/data-studio-sql-analysts/query-editor/using-snowflake-sql.md

description
Getting familiar with our SQL dialect.

Using Snowflake SQL

If you're familiar with common SQL dialects like Postgres or MySQL, you'll find that while there are a few specific differences, the basics will be very familiar, as the Snowflake SQL dialect is ANSI SQL compliant. (More on SQL standards and interoperability.)

Here's a roundup of some of the key differences people run into when switching from Postgres to Snowflake that we found helpful. In particular:

• Filtering in Snowflake must be done with CASE statements.
• No support for DISTINCT ON, so people use window functions, generally.

To help navigate this all of this, Snowflake also maintains a comprehensive SQL reference, and many Snowflake-specific functions are available. (Crypto analysts often find their JSON parsing functions can be particularly helpful.)