Amplitude
Databricks
| Feature | Amplitude | Databricks |
|---|---|---|
| Pricing | Free / from $49/mo | Free / from $0.07/mo |
| Free Plan | ✓ Yes | ✓ Yes |
| Rating | 4.4 / 5 | 4.5 / 5 |
| Best For | product-teams, growth-teams, data-analysts, saas-companies | data-engineering-teams, ml-teams, enterprises, large-scale-analytics |
| Founded | 2012 | 2013 |
| Event Analytics | ✓ | ✗ |
| Cohort Analysis | ✓ | ✗ |
| Funnels | ✓ | ✗ |
| Retention | ✓ | ✗ |
| Experimentation | ✓ | ✗ |
| Session Replay | ✓ | ✗ |
| Cdp | ✓ | ✗ |
| Data Lakehouse | ✗ | ✓ |
| Sql Analytics | ✗ | ✓ |
| Machine Learning | ✗ | ✓ |
| Real Time Streaming | ✗ | ✓ |
| Data Governance | ✗ | ✓ |
| Notebooks | ✗ | ✓ |
| Delta Lake | ✗ | ✓ |
✓ Amplitude Pros
- Powerful behavioral cohort analysis
- Free tier generous (50K monthly tracked users)
- Built-in experimentation (A/B testing)
- Excellent for product-led growth metrics
✗ Amplitude Cons
- Complex event taxonomy required upfront
- Expensive at scale beyond free tier
- Steep learning curve for non-analysts
✓ Databricks Pros
- Unified platform for data engineering, science, and analytics
- Delta Lake provides ACID transactions on data lakes
- Excellent ML/AI capabilities with MLflow integration
- Community Edition is free for learning
✗ Databricks Cons
- Complex pricing with DBU credits
- Requires data engineering expertise to configure
- Vendor lock-in once deeply integrated
The Verdict
Amplitude is built for product teams and growth teams, with a focus on event-analytics and cohort-analysis. Databricks targets data engineering teams and ml teams and leads with data-lakehouse and sql-analytics.
On pricing, Databricks is the clear winner for budget-conscious users — starting at $0.07/mo compared to $49/mo for Amplitude. That $48.93/mo difference adds up quickly for growing teams.
Both offer free plans, so you can test each with your real workflow before committing to a subscription.
This is a genuinely close comparison. If you can, sign up for both free trials (where available) and run a one-week test with your actual team tasks before deciding.