Good things:
- it's pretty fast (it does automatic partitioning of your data based on usage patterns, which is sweet)
- it integrates with your cloud storage pretty transparently
- the SQL dialect is pretty full-featured (it even has about half of PostGIS, which was useful to me recently)
- it's pretty fast, without custom tuning (which is annoying)
- the docs are pretty comprehensive, and they have a set of tutorials which are great (even if I only found them by accident).
Problems:
- No SparkSQL. Spark is super, super annoying, but the notion of PySpark and sparkr were pure genius. Why yes, of course I want to write my ETL in a real programming language (can define a function to remove 100+ case when statements.
- It's very, very expensive, and their purchasing model seems designed to prevent people from realising this.
- It's proprietary.
Not the OP, but this is why I like Snowflake (and I've been using solutions in the distributed SQL space for almost a decade at this point).