Use Snowflake when you need a powerful data warehouse with easy data sharing capabilities and you primarily deal with SQL-based analytics. You might choose Snowflake over Databricks when your organization has a strong focus on business intelligence (BI) tools that work well with SQL, and you require a straightforward experience for querying both structured and semi-structured data. For example, if a financial analytics team needs to generate reports quickly from a variety of data sources and share results seamlessly with external partners, Snowflake's ease of integration and data sharing features would be highly beneficial.
You would use Databricks Lakehouse Platform when you need a single platform for complex data engineering and machine learning tasks, especially when dealing with real-time data. For example, if your company is building a predictive analytics system that requires processing and analyzing streaming data from IoT devices in real-time, Databricks would provide a more suitable environment due to its native support for Apache Spark and real-time processing capabilities.