Snowflake and Databricks are converging into the same platform, feature by feature
Zachly · x · 2026-11-13
Over the past 12 months Snowflake and Databricks have been converging into essentially the same platform. One started as a cloud data warehouse, the other as a Spark-based data engineering and ML platform, but today they match each other feature for feature:
- dbt & SQL transformations: Snowflake ships dbt Projects on Snowflake, Workspaces, and enhanced dbt DAG lineage; Databricks offers dbt on Databricks, dbt tasks in Lakeflow Jobs, and Databricks SQL
- Declarative pipelines: Snowflake's Dynamic Tables (with custom incrementalization) vs Databricks' Lakeflow Spark Declarative Pipelines, materialized views, and streaming tables
- Semantic layers: Snowflake's Semantic Views and Semantic Studio vs Databricks' Unity Catalog Metric Views
- AI analytics agents: Snowflake's Cortex Analyst and more, with Databricks moving in parallel
The takeaway: the two data platforms are converging into the same unified analytics platform, and differentiation is shrinking.
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