Databricks on Make Enterprise
Databricks is a data or analytics platform. Warehouses, lakehouses and planning tools that other systems load into and read from. Here is what Make lists for it, what we build around it, and what to settle before you automate it.
What does Make list for Databricks?
Make's page lists 8 actions by name.
Actions
- Download a file from a Unity Catalog volume
- Execute a SQL statement
- Get a job run output
- Get a pipeline update status
- Get a SQL statement result
- Make an API call
- Run a job
- Upload a file to a Unity Catalog volume
Module lists change as Make updates the app. Treat this as a snapshot and confirm on Make's page before you scope work.
What do we build around Databricks?
These are the kinds of scenarios we build for data and analytics platforms. They describe our work, not features of Databricks.
- Scheduled loads and refreshes between source systems and the platform
- Alerts when a feed is late, empty or malformed
- Hand-offs of results to the tools teams read
- Planning-data round trips with finance and operations systems
Example flows
- A nightly job loads closed orders and alerts if the count looks wrong
- Model results are written back to the CRM for the owning team
- A finance plan is refreshed from the ledger on a schedule
What should you settle before automating Databricks?
Settle these before the first production scenario so builders can start without waiting on a later security review.
- Which side owns each table or dataset
- How a bad load is detected and rolled back
- Which credentials the scenarios use and how they are rotated
- How much data a scenario may move in one run
Platform-level controls such as SSO, roles, encryption and log retention are Make's own published terms; see make.com/security and our Make Enterprise page for how we scope against them. Make describes the Enterprise plan itself at make.com/enterprise.
Frequently asked questions
Can Make connect to Databricks?
Yes. Make has a Databricks app, and its page states that it is supported and maintained by Make. It is listed in Make's Enterprise integrations category. The modules and names on this page are what Make shows on its own Databricks page as of November 5, 2026, so check Make's page for the current list.
What do you build around Databricks?
We build the scenarios around it: scheduled loads and refreshes between source systems and the platform; alerts when a feed is late, empty or malformed; hand-offs of results to the tools teams read. Scope is set on a call, and each scenario is documented in plain language before hand-over.
What should we decide before automating Databricks?
Start with the guardrails: which side owns each table or dataset; how a bad load is detected and rolled back; which credentials the scenarios use and how they are rotated. Settling these first lets builders start without waiting on a security review later.
Does the connection need Databricks admin access?
That depends on what the scenarios do and on Databricks's own permission model. We aim for a dedicated service account with the narrowest role that works, and we record which scenarios write and which only read. Your Databricks administrator decides what that account may reach.
Consultants in a Box is a Make partner. This page is written by us and is not published by Make or by Databricks's vendor. Databricks, Make and related names are trademarks of their owners. Statements about Make's platform are the ones Make publishes.
Planning to automate Databricks?
Book a call. We map your systems to the pages here, agree the guardrails and give you a written scope and price afterwards.