Databricks
Unified lakehouse platform for data engineering, science, and AI
Overview
Unified data analytics platform combining data engineering, data science, and machine learning on a lakehouse architecture. Features Delta Lake, MLflow, and AI-powered SQL analytics with natural language querying.
Ehsan's Growth Verdict
The most complete data + AI platform if you can stomach the pricing complexity
Best for: Data teams running both analytics and ML workloads at scale
Key Features
- ✓Delta Lake storage layer
- ✓MLflow experiment tracking
- ✓Unity Catalog governance
- ✓AI-powered SQL assistant
- ✓Real-time streaming
Pros
- + Best-in-class for combining data engineering and ML
- + Open-source foundation (Spark, Delta, MLflow)
- + Scales from startup to enterprise without re-platforming
Cons
- − Complex pricing model that can spike unpredictably
- − Steep learning curve for teams without Spark experience
- − Vendor lock-in despite open-source claims
Pricing
| Plan | Details |
|---|---|
| Enterprise | Custom volume discounts |
| All-Purpose | $0.40/DBU |
| SQL Compute | $0.22/DBU |
| Jobs Compute | $0.07/DBU (standard) |
Best Use Cases
Ehsan's Growth Take
Databricks won the lakehouse war. If your data team is >5 people and you're doing both analytics and ML, nothing else gives you this combination in one platform. But assign someone to monitor your DBU spend weekly or you'll get a surprise bill.
Ehsan Jahandarpour
AI Growth Strategist & Fractional CMO
Forbes Top 20 Growth Hacker · TEDx Speaker · 716 Academic Citations · Ex-Microsoft · CMO at FirstWave (ASX:FCT) · Forbes Communications Council