Snowflake vs Databricks
Snowflake and Databricks represent two philosophies in the modern data stack. Snowflake optimizes for SQL analytics and data sharing at scale with a SaaS-friendly model. Databricks unifies data engineering, ML, and analytics on Apache Spark with Delta Lake, targeting data teams that need Python/Scala and machine learning pipelines alongside SQL.
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The data cloud vs The data and AI company.
| Feature | Snowflake | Databricks |
|---|---|---|
| Pricing from | Pay-as-you-go from $2/credit | Pay-as-you-go from $0.07/DBU |
| Pricing | Compute credits from $2/credit | DBUs from $0.07/DBU; varies by workload type |
| Best for | SQL analytics, data sharing, and BI workloads | Data engineering, ML, and unified analytics |
| Programming language | SQL primary, Snowpark (Python/Java/Scala) | Python, Scala, SQL, R on Spark |
| Machine learning | Snowpark ML, Cortex AI | MLflow, AutoML, Feature Store built-in |
| Data lake support | Iceberg and Delta Lake external tables | Delta Lake native, Lakehouse architecture |
| BI tool integration | Excellent with Tableau, Looker, Power BI | Good, especially with partner BI tools |
The third option most teams miss
Picking between Snowflake and Databricks isn't the only choice.
Appaca orchestrates data workflows across Snowflake and Databricks, letting your SQL analysts query Snowflake while your ML engineers train on Databricks-with unified lineage, cost tracking, and governance in one platform.
- No code, no deployment, no devops
- Built-in database, dashboards, team access
- Refine with chat as your needs change
- Free to start, no per-seat pricing surprises
Common questions
If your primary use case is SQL analytics and business intelligence, Snowflake is the simpler choice. If you need data engineering pipelines, machine learning, and real-time streaming alongside analytics, Databricks' unified platform is more powerful.
Databricks SQL Warehouse is a capable SQL analytics alternative to Snowflake. However, Snowflake's data sharing capabilities, time travel, and easier governance model still give it advantages for pure analytics.
The Databricks Lakehouse combines data lake flexibility (Delta Lake on object storage) with data warehouse performance and ACID transactions. It aims to replace the two-tier data lake + data warehouse architecture with a single platform.