Databricks AI from Databricks trains, serves, and governs models on the same lakehouse as analytics workloads. It is aimed at enterprises unifying data and AI, with a consumption-based DBUs with AI features billed on top of compute. Expensive and complex for teams without existing Spark expertise. Editorial teams should verify fit against their compliance and workflow needs before rolling it out broadly.
Databricks
Databricks AI
Lakehouse platform with Mosaic AI models
PaidScore 77.1#56 overall#2 in AI Infrastructure
140 editorial upvotes · editor score 4.3 / 5
Specs
| Pricing | Paid |
|---|---|
| Starting price | — |
| Free tier | No |
| Platforms | Web, API |
| Launched | Jun 1, 2013 |
| Last verified | Oct 18, 2026 |
| Vendor | Databricks |
Highlights
- Lakehouse integration
- Mosaic models
Pros
- Unified data+AI
- Enterprise governance
Cons
- High complexity
Alternatives
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- MLflowOpen platform for ML lifecycle management72.8
Reviews
Reviews open in the next release. Editor scores on this page are editorial estimates, not user ratings.