SQL converter
Rewrite quoting, escaping, row limits and function names between 16 dialects, with a list of what it refused to guess at.
Apache Spark SQL query
Amazon Athena / Trino query
What it changed
current timestampCURRENT_TIMESTAMP1 place
What you still need to do
1 thing this tool will not guess at
Array subscript
Apache Spark SQL counts array positions from 0, Amazon Athena / Trino from 1: the same arr[1] is the first element in one and the second in the other, with no error. Adjust every index by one.
Anything left in this list was recognised and left as it was on purpose. A function renamed to one that takes its arguments in a different order produces SQL that runs and returns the wrong rows, which is worse than SQL that fails.
Converting Apache Spark SQL to Amazon Athena / Trino: Key Syntax Differences
Translating SQL queries between Apache Spark SQL and Amazon Athena / Trino involves subtle dialect differences that standard text find-and-replace often misses. Everything below is processed entirely in your browser using SQLParity.
Identifier Quoting
Apache Spark SQL: `name`
Amazon Athena / Trino: "name"
String Literal Escaping
Apache Spark SQL: Quotes are escaped with backslash (\'), backslash is an escape character.
Amazon Athena / Trino: Quotes are doubled (''), backslash is literal.
Null-Safe Equality
Amazon Athena / Trino: colA IS DISTINCT FROM colB
Why In-Browser SQL Conversion Matters
Database migrations frequently involve proprietary business logic, sensitive table schemas, and production column names. When converting SQL between Apache Spark SQL and Amazon Athena / Trino, SQLParity executes all parsing, tokenization, and code rewriting locally in your browser. Zero queries or schemas are transmitted to remote servers.