Snowflake vs Databricks
Complete technical comparison for data platform selection in 2025
TL;DR: Which Should You Choose?
Choose Snowflake if:
You need a traditional data warehouse for BI/analytics, have strong SQL teams, prioritize ease of use, and don't need heavy ML workloads.
Choose Databricks if:
You're building ML/AI products, need real-time streaming, have data science/engineering teams, or want lakehouse architecture flexibility.
Use Both if:
You're enterprise-scale with distinct analytics (Snowflake) and ML (Databricks) workloads. Many Fortune 500s do this.
Head-to-Head Comparison
| Category | ❄️ Snowflake | 🧱 Databricks | Winner |
|---|---|---|---|
| Architecture | Pure cloud data warehouse. Compute & storage separated. | Lakehouse architecture. Unified batch & streaming on Delta Lake. | 🧱 Databricks |
| Primary Use Case | Analytics, BI, data warehousing | ML/AI, data science, real-time analytics | 🤝 Tie |
| SQL Performance | Excellent for structured data queries | Good, improving with Photon engine | ❄️ Snowflake |
| ML/AI Capabilities | Limited. Snowpark ML is new. | Industry-leading MLflow, AutoML | 🧱 Databricks |
| Pricing Model | Credits-based. Can be unpredictable. | DBU-based. Requires careful optimization. | 🤝 Tie |
| Ease of Use | Very SQL-friendly. Lower learning curve. | Steeper curve. Requires Spark knowledge. | ❄️ Snowflake |
| Data Governance | Strong RBAC, data sharing, governance features | Unity Catalog improving governance | ❄️ Snowflake |
| Real-time Streaming | Snowpipe (micro-batch). Limited streaming. | Native streaming with Structured Streaming | 🧱 Databricks |
Pricing Breakdown
Snowflake
Model:
Credits consumed per second of compute
Typical Cost:
$2-$4 per credit (varies by cloud/region)
Small Warehouse:
2 credits/hour = $4-8/hour
Storage:
~$23-40/TB/month
⚠️ Watch Out:
Auto-suspend is critical. Costs spike fast without it.
Databricks
Model:
DBUs (Databricks Units) + cloud compute
Typical Cost:
$0.07-0.55 per DBU (tier-dependent)
All-Purpose Cluster:
~$1-6/hour (depends on instance type)
Storage:
Cloud storage costs (S3/ADLS/GCS) ~$20/TB/month
⚠️ Watch Out:
Job vs. All-Purpose pricing differs 2-3x. Use Jobs clusters.
💰 Real-World Budgets
Small team (5-10 data folks): $5K-15K/month either platform
Mid-market (20-50 people): $20K-80K/month
Enterprise (100+ people): $150K-500K+/month
Decision Framework by Use Case
📊 Traditional BI & Analytics → Snowflake
If your primary need is SQL queries, dashboards (Tableau/Power BI), and structured reporting, Snowflake's simplicity wins.
🤖 ML/AI & Data Science → Databricks
Model training, feature engineering, MLOps? Databricks' notebook environment and MLflow integration are unmatched.
⚡ Real-Time Streaming → Databricks
Kafka, event processing, real-time features? Databricks' Structured Streaming is purpose-built for this.
📈 Mixed Workloads → Consider Both
Analytics in Snowflake, ML in Databricks, connected via Delta Sharing or S3. Common at enterprise scale.
Migration Paths
From On-Prem Warehouse → Snowflake
- Assess current EDW (Teradata, Oracle, SQL Server)
- Schema migration planning (ER Studio, Erwin)
- Use Snowflake's migration services/partners
- Parallel run & cutover (typically 3-6 months)
⏱️ Timeline: 4-9 months for medium complexity
From Data Lake → Databricks
- Convert existing S3/ADLS to Delta Lake format
- Migrate Spark jobs to Databricks workflows
- Consolidate notebooks & ML pipelines
- Incremental adoption (can run alongside existing)
⏱️ Timeline: 2-6 months for incremental approach
Need Help Migrating?
Compare 50 data engineering companies with Snowflake and Databricks expertise.