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About AQL

AQL is both a query language and a metric definition language. It leverages the data semantic model defined with AML to allow you to query your data in a higher abstraction manner, especially composing and reusing metric-based queries.

With AQL, you can quickly implement analytics use cases that are typically complicated in SQL. Things like Percent of Total, Nested Aggregations, Level of Details, among other things.

AQL is designed based on Metrics-centric Thinking paradigm. In AQL, metrics are elevated to first-class status, which means they can be defined, manipulated and reused, independently from tables and models.

When executed, AQL compiles to SQL and thus works with most databases that use SQL. Currently supported databases are PostgreSQL, Amazon Redshift, Google BigQuery, Snowflake, Databricks, Microsoft SQLServer, Clickhouse; and more are being added.

Documentation Structure

AQL documentation are organized into the following sections:

Where to go next

To get started with AQL, please follow the documentation at Getting Started with AQL. To learn more about AQL, please read Learning AQL.

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