While Snowflake has been leaning on its Cortex and Native App Framework to let enterprises build AI-powered applications and agents closer to governed data, Databricks has been focusing on agent workflows through Mosaic AI, emphasizing model development, orchestration, and evaluation tied to its lakehouse architecture, Robert Kramer, principal analyst at Moor Insights and Strategy, said.
Seconding Kramer, Walter pointed out that Teradata’s differentiation lies in positioning Enterprise AgentStack as a vendor-agnostic execution and operations layer designed to work across hybrid environments, rather than anchoring agents tightly to a single cloud or data platform.
That positioning can be attributed to Teradata’s reliance on third-party frameworks such as Karini.ai, Flowise, CrewAI, and LangGraph, which give enterprises and their developers flexibility to evolve their agent architectures over time without being locked onto platforms from Snowflake and Databricks that tend to optimize for end-to-end control within their own environments, Walter added.
