How is Databricks priced?

Databricks is priced on consumption across Databricks Units (DBUs). DBU rate varies by tier (Standard, Premium, Enterprise), workload type (All Purpose Compute, Jobs Compute, Databricks SQL, Serverless), and cloud. Underlying cloud compute is billed separately.

Should we accept a Databricks committed use commitment?

Often yes. The broader committed dollar framework drives the broader tier discount framework. The buyer side framework requires the broader rollover protection, the broader true forward management, and the broader unused commitment protection.

What discount range is realistic?

Twenty to forty five percent off the broader pay as you go framework is realistic at the broader enterprise scale, with deeper discounts at three year committed dollar levels and where Snowflake or Microsoft Fabric bake offs are credible.

Should we run Databricks on AWS, Azure, or GCP?

The broader cloud burndown framework matters. On Azure, Azure Databricks is a Microsoft first party service that burns down MACC dollars. On AWS and GCP, Databricks burns down via the marketplace framework.

Databricks Negotiation: White Paper

Databricks is the load bearing Databricks Lakehouse Platform framework, anchoring the broader cloud data and AI platform framework against the broader Snowflake, BigQuery, Redshift, and Microsoft Fabric market. Databricks segments the broader framework across the broader Databricks Standard tier framework, the broader Databricks Premium tier framework, the broader Databricks Enterprise tier framework, the broader Databricks Serverless framework, the broader Databricks SQL framework, the broader Databricks Mosaic AI framework (broader generative AI framework), the broader Databricks Unity Catalog framework, the broader Databricks Delta Live Tables framework, the broader Databricks Workflows framework, the broader Databricks compute (DBU) consumption framework, the broader Databricks committed use framework, and the bespoke framework at the upper customer scale. This paper sets out the buyer side framework for Databricks negotiation. Read the related Vendor Shield, the renewal program, the AWS EDP negotiation, the AI platform contract negotiation, and the benchmarking practice.

What you will learn

The eleven move buyer side framework
Databricks tiers framework: Standard, Premium, Enterprise
Databricks Units (DBU) consumption framework
Databricks committed use framework
Databricks Mosaic AI framework
Databricks Unity Catalog framework
Cloud burndown framework: AWS EDP, Azure MACC, GCP CUD
Competitive framework: Snowflake, BigQuery, Redshift, Microsoft Fabric

Databricks Negotiation

The tiers framework
The DBU framework
The committed use framework
The Mosaic AI framework
The Unity Catalog framework
The cloud burndown framework
The eleven move negotiation framework

Who this is for

['CIOs and procurement leaders facing a Databricks renewal', 'Data and AI platform leaders evaluating Databricks versus Snowflake', 'Cloud commercial owners managing AWS EDP, Azure MACC, GCP CUD', 'AI platform leaders sizing Mosaic AI against the broader generative AI framework']

White Paper · Databricks