Databricks Mosaic AIEnterprise
Databricks' suite for building, governing, and serving production AI — agents, RAG, fine-tuning, and evaluation — on top of your governed data.
AI Infrastructure comparison
Databricks Mosaic AI vs Portkey
Pricing, pros, cons, and ideal use cases — side by side.
PortkeyFreemium
An AI gateway that adds routing, caching, observability, and guardrails to LLM traffic through a single control plane.
At a glance
| Databricks Mosaic AI | Portkey | |
|---|---|---|
| Pricing | EnterpriseConsumption-based, billed within the Databricks platform; enterprise agreements typical. | FreemiumFree developer tier. Paid Pro and Enterprise plans add volume, self-hosting, and governance. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Enterprises building AI on the Databricks lakehouseData teams that want AI governed alongside dataOrganizations unifying data and AI on one platform | Enterprises standardizing LLM access across teamsPlatform teams needing routing and failoverOrgs wanting cost and reliability controls in one place |
Pros & cons
Databricks Mosaic AI
Pros
- AI built directly on governed lakehouse data
- Unity Catalog lineage and access control extend to AI
- Covers agents, RAG, fine-tuning, serving, and evals
- Strong fit for data-mature enterprises
Cons
- Most valuable only on the Databricks platform
- Platform commitment, not a point solution
- Enterprise pricing and procurement
Portkey
Pros
- Routing, failover, and caching out of the box
- Built-in observability and cost analytics
- Guardrails enforced at the gateway
- Managed or self-hosted
Cons
- Another vendor in the critical request path
- Overlaps with observability tools you may already run
- Full governance features need a paid plan
Which should you choose?
Portkey is the lighter-weight option (Freemium), while Databricks Mosaic AI sits higher on the pricing ladder (Enterprise). Databricks Mosaic AI is built around enterprises building ai on the databricks lakehouse; Portkey leans more toward enterprises standardizing llm access across teams. Shortlist the one whose strengths line up with your biggest constraint.