We have shipped production RAG on Snowflake Cortex and on Databricks Mosaic AI at six regulated enterprises. Here is what we learned — without the marketing.
The headline: both work. The differences are about data gravity, team skills, and where the AI lives relative to the data.
Snowflake Cortex wins when the warehouse IS the system of record. If your customer data, documents and operational data already live in Snowflake, Cortex Search + Cortex Analyst is the lowest-friction path. The vector index is Delta-backed inside Snowflake, the SQL tool calling is native, and the cost is per-credit (transparent).
Databricks Mosaic AI wins when the lakehouse IS the system of record. If you already have a Databricks lakehouse with Delta tables, MLflow and Unity Catalog, Mosaic AI is the path of least resistance. Vector Search over Delta, AI Functions for SQL/Python, Model Serving, AI Playground, Agent Framework — all in one platform.
Vector retrieval. Cortex Search is solid for hybrid retrieval with reranking. Databricks Vector Search is newer, also solid, with closer integration to Mosaic AI Agent Framework. We have shipped both in production with retrieval latency under 100 ms p95 at 10 M+ vectors.
Reranking. Cortex has native reranking. Mosaic AI integrates with external rerankers (Cohere, Snowflake Cortex, custom). For regulated enterprises with vendor constraints, the native option is the safer bet.
Tool calling & agents. Cortex Agents (GA in 2025) is a strong multi-agent runtime. Mosaic AI Agent Framework (GA in 2024) is more mature. Both support MCP, both support function calling, both have memory and observability.
Observability. Cortex has native observability via Snowflake telemetry. Mosaic AI has MLflow tracing. Both integrate with LangSmith / Langfuse / Arize Phoenix. We standardise on MLflow for Mosaic and Snowflake telemetry for Cortex.
Cost. Both are per-token + per-storage. Cortex tends to be cheaper for small-to-medium RAG; Mosaic AI tends to be cheaper for large RAG with heavy ML on top. Run the numbers — don’t trust the marketing.
Data residency. Snowflake has strong EU / APAC / government cloud coverage. Databricks has the same. Both meet GDPR, HIPAA, PCI-DSS, FedRAMP. Verify per region.
When to pick which:
– Pure RAG, data already in Snowflake → Cortex. Lowest friction.
– Heavy ML, data already in Databricks → Mosaic AI. Native.
– Polyglot estate → pick the one with the bigger data gravity, or use both via Federation.
– Cost-sensitive RAG → run a benchmark. Don’t trust benchmarks from either vendor.
Our honest take: both are production-grade. Pick the one your data team already knows. The differentiator is the team, not the platform.