Snowflake vs Databricks: A Comprehensive Comparison

As data continues to grow in importance and complexity, data analysts and data scientists need to leverage the most suitable tools to derive valuable insights. In this comprehensive comparison, we will explore two of the most popular data platforms: Databricks and Snowflake[4]. We will examine their features, benefits, and drawbacks to help you make an informed decision about the right tool for your needs.

Background

Traditionally, corporations used data warehouses to store data of various types generated from various sources. However, with the evolution of technology, data needs have changed because of increased data velocity, volume, and veracity[1]. Both Databricks and Snowflake are designed to scale with your data needs, but they have some key differences in their features and functionalities[4].

Key Differences

Here are some of the main differences between Databricks and Snowflake:

- **Service Model**: Databricks operates as a Platform as a Service (PaaS), while Snowflake is a Software as a Service (SaaS) offering[1].
- **Major Cloud Platform Support**: Databricks supports Azure, AWS, and Google, while Snowflake supports Azure, AWS, and Google[1].
- **Migration to Platform**: Migrating to Databricks is complex because it is a data…