Nearly every technology leader in ETR's Databricks Edge Report plans to spend more, as AI use cases multiply and the lakehouse absorbs work once spread across several tools.

Ask technology leaders why their Databricks spend is changing, and the answer points one way. ETR's Databricks Edge Report gathered qualitative commentary from 26 technology leaders, and 24 of them plan to increase spend over the next six months. Only two plan to cut back.

AI workloads are the most common driver, data volumes keep climbing, and more organizations are folding analytics, engineering, and governance onto a single platform. Underneath it all runs one caveat: cost.

Key Takeaways

• AI is the dominant driver. Seventeen of 24 increasers cite AI impact, from agentic and LLM workloads to model training and conversational analytics.

• Data growth keeps the meter running. Business growth is a theme for 15 increasers, many describing rising data volumes rather than brand-new projects.

• Consolidation favors Databricks. Several increasers are retiring legacy warehouses, ETL tools, and rival platforms, positioning Databricks as their core data backbone.

• Cost is the watch item. Consumption pricing climbs with adoption, and both decreasers are moving budget to alternatives.

AI Is the Engine

For many increasers, AI means agentic and LLM workloads running on a consolidated foundation. A VP at an APAC Global 1000 IT/TelCo company described Databricks as "a unified platform which is combining our data engineering, data science and business analytics into single lakehouse architecture."

Conversational AI adds another layer of demand. One Fortune 1000 organization is rolling out Genie to give users natural-language access to data, with a predictable side effect: "We see the costs going up with more users trying the NLP capabilities."

Much of this growth is net new. More than half of increasers say the added spend is not coming at another vendor's expense, a sign that Databricks is expanding its share of the data budget rather than winning a zero-sum swap.

Data Growth Keeps the Meter Running

Alongside AI, the simplest driver is volume. "We are using Databricks' products more and we have more and more data generated from the enterprise," said a Senior Practitioner at a North American Fortune 100 IT/TelCo company. For one services firm, the pull extends to its own clients: "It is now the first choice tool for most of our customers for big data solutions."

The Lakehouse Absorbs the Stack

Several increasers are retiring legacy warehouses, regional data hubs, and traditional ETL tools, and at least one is weighing a move off a rival cloud warehouse entirely. "Snowflake is the largest one and we are looking at how we can move all to Databricks," said a C-level leader at a large North American Financials/Insurance company.

The ambition is often sweeping. A Director at a Fortune 100 Retail/Consumer company said Databricks "will be our tool for everything data." Governance adds to the appeal in regulated industries, where a Director at a small North American organization credited Unity Catalog's "unified governance, end-to-end data lineage, and monitoring across all of our data and AI assets."

Once embedded, Databricks is hard to dislodge. "Switching cost is high, and we are happy with Databricks," said a C-level leader at a midsize Services/Consulting company.

Cost Is the Caveat

Not every account is all-in. A Director at a large Industrials/Materials/Manufacturing company, moving from proof of concept to production, is still weighing a hyperscaler alternative: "Databricks is a complete solution but cost could be a factor."

The two decreasers tell different stories. One is shifting some budget to AI vendors for data cleansing while keeping Databricks as its enterprise data platform. The other is moving to an in-house warehouse and AI tools to reduce SaaS costs, with plans to phase Databricks out entirely.

What It Means

Databricks looks strongest where AI ambition meets data sprawl. Organizations want one platform for engineering, analytics, governance, and model work, and for most of this panel, Databricks is becoming that platform. The risk is that consumption pricing scales as fast as adoption, and cost-conscious buyers have options.

Access the Databricks Edge Report

The August 2026 Databricks Edge Report details every account's commentary, including which platforms Databricks is displacing and where decreasers are moving budget. Discover which rivals are ceding workloads to the lakehouse by contacting service@etr.ai.