Overview
Databricks, created by the founders of Apache Spark, pioneered the data lakehouse paradigm. It combines the best of data lakes and warehouses on a unified platform. With Delta Lake, Unity Catalog, and built-in ML capabilities, it's the leading platform for large-scale data engineering and AI.
Key Features
- ✓ Lakehouse Architecture: Open formats + ACID transactions
- ✓ Delta Lake: Open-source storage layer with reliability
- ✓ Unity Catalog: Unified governance across data and AI
- ✓ SQL Warehouses: Serverless SQL analytics
- ✓ MLflow Integration: End-to-end ML lifecycle
- ✓ Notebooks: Collaborative data science environment
Pros
- 👍 Most powerful platform for large-scale data
- 👍 Best-in-class Spark performance
- 👍 Strong data science/ML capabilities
- 👍 Open formats (Delta, Iceberg support)
- 👍 Active innovation (fastest-moving vendor)
Cons
- 👎 Complexity for simple use cases
- 👎 Cost can escalate quickly
- 👎 Learning curve is steep
- 👎 DBU pricing is confusing
- 👎 Vendor lock-in concerns despite open formats
Best For
Large enterprises with complex data engineering and ML needs. Ideal when you need both batch and streaming, or are building data products at scale.
Founded: 2013 HQ: San Francisco, CA