
Here’s a clear, updated comparison of Databricks Paid Edition vs. Free Edition (2025):
Databricks Paid Edition vs. Free Edition
Feature / Aspect | Free Edition | Paid Edition |
---|---|---|
Cost | Free | Billed (pay-as-you-go or subscription) |
Cluster Size | Small, limited resources | Scalable clusters, large instance types, autoscaling |
Session Limits | Limited (e.g., timeouts, max sessions) | Unlimited/longer session time |
Users/Collaboration | Single user | Multi-user, team collaboration, role-based access |
Data Storage | Limited storage (quota, file size) | Full cloud storage (S3, ADLS, GCS) |
Compute Types | Limited compute options | All compute types (standard, high memory, GPU, etc.) |
Workspaces | One per user | Multiple, with granular access control |
SQL Warehouses | Limited or not available | Full SQL warehouses (Classic, Pro, Serverless) |
Unity Catalog | Not available | Full data governance (Unity Catalog) |
Delta Lake | Basic (for learning) | Full features, ACID, time travel, advanced options |
Delta Live Tables | Not available | Yes, for production ETL pipelines |
Mosaic AI/LLM | Not available or restricted | Yes, for GenAI and LLM workflows |
Machine Learning | Basic support | Full ML/AI platform (MLflow, AutoML, Model Serving) |
Jobs & Orchestration | Limited or not available | Full jobs, scheduling, orchestration (Workflows) |
External Integrations | Minimal | Full (Power BI, Tableau, REST API, Git, etc.) |
Data Sharing | Not available | Yes (Delta Sharing, cross-org/data mesh) |
Security & Governance | Basic | Enterprise RBAC, audit, SSO, fine-grained control |
Support | Community only | Professional support, SLAs |
Production SLAs | No | Yes |
In Short:
- Free Edition:
- Great for learning, testing, and demos.
- Single-user, small resources, limited features.
- No production use, advanced security, or team collaboration.
- Paid Edition:
- Full-featured, production-ready.
- Scalable compute, enterprise governance, collaboration, ML/AI, automation, security, support.
- Suitable for business-critical and large-scale workloads.
