Snowflake is often chosen for its flexible architecture and support for various cloud environments. You would use Snowflake over BigQuery in scenarios where you need to run a high volume of concurrent queries with consistent performance. For example, if you have a multi-cloud strategy and want to leverage data from both AWS and Azure seamlessly, Snowflake would be a better fit.
BigQuery is an excellent choice when you need to handle large-scale data analysis effortlessly without managing infrastructure. It's particularly useful in scenarios where you are already using Google Cloud services, such as a data pipeline that ingests data into Google Cloud Storage, processes it in Dataflow, and requires analysis in BigQuery. For instance, if you're running a marketing analysis on user behavior from data collected in Google Analytics, using BigQuery can streamline the process due to its tight integration with other Google services.