Hello,
 When evaluating data quality frameworks for PySpark pipelines, I came across DQX. I noticed it's available on PyPI (databricks-labs-dqx) and GitHub, which is great for accessibility.

However, I'm trying to understand the licensing requirements. The LICENSE information on PyPI mentions it as "Other/Proprietary", and the license file on GitHub states that the materials can only be used "in connection with your use of the Databricks Services."

I would like to understand,

1. Does this mean DQX requires a Databricks platform agreement even when used in other Spark environments (e.g., AWS EMR, Dataproc, or standalone Spark clusters)?
2. If a Databricks agreement is required, are there specific licensing options for using Labs projects outside the Databricks platform?
3. Are there any recommended alternatives for data quality validation in non-Databricks PySpark environments that you'd suggest?

I want to ensure we're compliant with all licensing requirements before adopting any framework. Any clarification would be greatly appreciated.

Thanks in advance!
Kiran