Position Databricks Across Cloud Models

Company Context

Databricks is a leading data and AI platform company operating across AWS, Azure, and Google Cloud. Its core offering, the Databricks Data Intelligence Platform, includes capabilities such as Delta Lake, Unity Catalog, Databricks SQL, Mosaic AI, and Apache Spark-based data engineering and machine learning workflows. Databricks increasingly sells into enterprises that are rationalizing fragmented analytics stacks and deciding how much infrastructure they want to manage themselves.

Strategic Situation

You are an Account Executive at Databricks preparing for a regional planning review. Several CIOs in your territory are asking a basic but commercially important question: how do IaaS, PaaS, and SaaS differ, and where should Databricks position itself relative to each model? The challenge is not just to define the terms, but to turn that understanding into a practical account strategy. Databricks needs a clear narrative for when to position against raw cloud infrastructure, when to coexist with cloud-native platform services, and when to displace point SaaS analytics tools.

Your VP wants a recommendation for how Databricks should prioritize its sales motion over the next 12 months for mid-market and enterprise accounts that are modernizing their data estates.

Data Points

Additional observations:

• Win rate is currently 18% in IaaS-led modernization deals, 28% in PaaS expansion deals, and 22% in SaaS displacement deals.
• Gross margin is strongest in enterprise standardization motions because workloads expand over time.
• Product marketing can only support two primary plays this year.

Deliverables

1. Explain the strategic difference between IaaS, PaaS, and SaaS, using Databricks-relevant examples.
2. Assess which customer segment(s) Databricks should prioritize: IaaS-led modernization, PaaS consolidation/expansion, or SaaS displacement.
3. Estimate the near-term revenue opportunity for each motion using the data above.
4. Recommend a 12-month go-to-market focus and explain the trade-offs.
5. Outline how an AE should tailor the Databricks value proposition for each cloud model.

Constraints

• Only two GTM plays can receive full enablement and marketing support this year.
• Budget for incremental regional investment is capped at $1.5M.
• Leadership expects measurable ARR impact within 12 months, not a multi-year transformation thesis.
• Recommendation must work across AWS, Azure, and Google Cloud rather than relying on a single hyperscaler partnership.