Snowflake is particularly useful when you need a cloud-based data warehouse that can handle large volumes of data, support complex queries, and allow easy collaboration with other teams or organizations. For instance, if a company needs to analyze extensive historical data while collaborating with external partners without moving the data, Snowflake's data sharing capability would be preferred over Druid's focus on real-time analytics.
Druid is designed for high-speed analytics on large datasets with the ability to ingest and process real-time data. It's suitable for scenarios where you need immediate insights into streaming data. For example, if you are monitoring IoT sensors and need to visualize and analyze that data in real-time, Druid would be a better choice than Snowflake, which is more suited for batch processing and slower queries.