Snowflake vs Databricks: which is better for data processing and analytics workloads?

Snowflake and Databricks are both powerful platforms for data processing and analytics but have different strengths:

  • Snowflake: Known for its performance and scalability and is highly suited for data warehousing and analytics. It’s optimized for SQL-based analytics and integrates well with tools like dbt for transformation tasks.
  • Databricks: Best known for its capabilities in machine learning, Databricks is excellent for big data processing and AI/ML workloads. It supports both batch and stream processing with Apache Spark, making it ideal for advanced analytics use cases.

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