Databricks
Databricks is the platform to pick when your AI work starts from large, messy, governed data and your team already thinks in Spark, SQL and notebooks; the model training, serving and agent tooling sit on the same tables as the pipelines, which is the whole point. It is not a tool you try on a Saturday: pricing is in DBUs across three clouds, and a small team wanting a hosted model endpoint will find simpler and cheaper routes.
Pros
- One governed data layer (Unity Catalog) spans pipelines, warehousing, training and serving
- Runs on AWS, Azure and Google Cloud, with the open Delta Lake format underneath
- Mosaic AI adds fine-tuning, vector search, model serving and agent evaluation without moving data
- Free Edition gives full-platform access for learning at no cost
- Per-second pay-as-you-go billing and a 14-day trial, no up-front commitment
Cons
- DBU-based pricing is hard to forecast and varies by cloud, region and workload type
- The platform assumes data-engineering skills; the learning curve is steep for application developers
- Free Edition is personal and non-commercial, with smaller compute and fair-use limits
- Real costs often come from the underlying cloud compute on top of the DBU charge