🧑‍💻 Supercharge AQL with SQL Passthrough

Have you ever received JSON data in your dataset and wished you could unnest it right there, without having to go back and modify your data model?

Previously, you'd need to:

• 🔙 Navigate back to the model
• 🛠 Create a SQL dimension
• ✍ Write custom SQL just to extract fields

Why? Because AQL doesn't yet have built-in support for these database-specific functions (like JSON unnesting).

Now, with SQL Passthrough for AQL, you can do this directly in your dataset! 🎉

No more back-and-forth — just write AQL and leverage native SQL functions to handle JSON (and much more).

This isn’t limited to JSON unnesting — any database-specific functionality not available in AQL can now be tapped into using passthrough.

👉 How it works: SQL Passthrough functions act as a bridge, letting you call native SQL functions from your underlying database while maintaining type safety inside AQL queries.

That means you can:

• Extract fields from JSON directly in your dataset
• Apply database-specific functions (Postgres, BigQuery, MySQL, etc.)
• Extend the power of AQL without breaking your workflow

For more details, you can visit our public doc about SQL Passthrough