Choosing between these platforms depends on your specific use cases, technical requirements, and organizational preferences.

Scale and architecture considerations:

• Snowflake and BigQuery: Excellent for large-scale data warehouses with strong SQL analytics capabilities
• Databricks: Ideal for big data processing, machine learning, and advanced analytics workloads
• All platforms integrate well with Snowplow's event pipeline for granular, first-party data processing

Use case optimization:

• Databricks: Better for real-time analytics, ML model development, and complex data science workflows
• Snowflake and BigQuery: Excel in batch analytics, business intelligence, and traditional data warehousing
• BigQuery: Strong integration with Google Cloud ecosystem and excellent for analytics at scale

Integration and ecosystem:

• Consider which platform integrates best with your existing data ecosystem and tools
• Evaluate available connectors, APIs, and third-party tool support
• Assess long-term strategic alignment with your cloud and technology choices