Resources · Make integration

Databricks Make integrationAutomate Databricks with Make.

Can Make start your Databricks work without a line of code? The Databricks Make integration gives you 6 action modules for SQL, jobs, pipelines and files. It suits data and ops teams on the Enterprise plan, and this page walks you from connection to a working scenario.

Enterprise app This app is reserved to Make's Enterprise plan.

Try the Databricks integration on MakeSee the 6 modules

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What you can automate

What can the Databricks Make integration do for you?

The Databricks Make integration lets a Make scenario (the automation you build, a chain of modules) send work to your Databricks workspace: run a SQL statement, start a job, check a pipeline update or drop a file into a Unity Catalog volume. It has no trigger, so another app or a schedule starts the flow.

Launch a job when something happens elsewhere. A form is submitted or a record changes in another app, and Run a job starts the matching Databricks job. Add Get a job run output after it to pull the result back into the scenario and pass it on.

Feed a volume with incoming files. A file lands in your storage app, and Upload a file to a Unity Catalog volume places it where your notebooks and tables expect it, with no manual download and re-upload.

Answer a question with SQL. Execute a SQL statement sends a query, Get a SQL statement result fetches what came back, and the next module can write it to a sheet or a message. Pipeline owners can use Get a pipeline update status to know where an update stands.

Two limits shape the setup: the app is reserved to the Make Enterprise plan, and the service principal behind the connection only sees the jobs, pipelines, catalogs and volumes it has been granted. If you also work with n8n, the Databricks n8n integration covers the same app, and n8n vs Make helps you pick. New to the editor? The Make training starts from zero.

Connect

How do you connect Databricks to Make?

  1. 01

    Collect three values in Databricks

    Copy your workspace URL from the browser bar. Then open Settings > Identity and access > Service principals, select yours, copy the Application ID, and in the Secrets tab generate or copy an OAuth secret. Keep all three somewhere safe.

  2. 02

    Open the connection window in Make

    Add any Databricks module to your scenario and click Create a connection. A connection is your Databricks account linked to Make once, then reused by every Databricks module. You can give it a name in Connection name.

  3. 03

    Paste the values and save

    Put the workspace URL in Workspace URL, the Application ID in Client ID and the OAuth secret in Client secret, then click Save. If Databricks asks you to authenticate and confirm access, do it and you are done.

First scenario

Your first scenario: start a job and read its output

GoalWhen another app sends a request, Make starts a Databricks job and brings its output back into the scenario.

  1. 01

    Create the scenario

    From the Scenarios page, create a new scenario and click the +. Pick the app that should start the flow, or keep a schedule on the first module if nothing needs to wait for an event.

  2. 02

    Add Run a job

    Click the + on the right of that first module, search for Databricks and choose Run a job. Select your connection, or create it with the three values from the previous section, then fill the module fields.

  3. 03

    Chain Get a job run output

    Add Get a job run output after it and map the run details that Run a job returned. Each item passed along this way is a bundle, and each module execution counts as one operation on your plan.

  4. 04

    Test with Run once

    Click Run once. Make executes the scenario a single time and shows the bundles each module received, so you can check that the job started and what came back.

  5. 05

    Schedule and switch on

    Set the schedule on the first module if it is scheduled (every 15 minutes by default on a new scenario), then switch the scenario on. From now on it runs without you.

Modules

What each Databricks module does

Databricks gives you 6 modules in 4 groups. For each one: what it does for you, when to reach for it, and what to watch out for.

SQL

2 modules
Databricks1

Execute a SQL statement

ActionIn the docs only

Sends a SQL query to your Databricks workspace from inside a scenario, so data questions and updates can follow an event in another app instead of waiting for someone to open a notebook.

When to use it
a new order or a finished import should update a table or count rows right away.
Watch out
the service principal needs rights on the catalog you query, otherwise the statement fails.
Databricks2

Get a SQL statement result

ActionIn the docs only

Brings the answer of a SQL statement back into Make, so the next module can put the rows into a spreadsheet, a report or a chat message for the people who asked.

When to use it
right after Execute a SQL statement, when the numbers must leave Databricks and reach a business tool.
Watch out
map the statement details from the previous module rather than typing them, which should let each run fetch the result of its own query.

Jobs

2 modules
Databricks3

Run a job

ActionIn the docs only

Starts one of your existing Databricks jobs on demand, which turns a manual click in the workspace into a step that fires when the business event actually happens.

When to use it
fresh data has arrived in another tool and the processing job should start without anyone watching.
Watch out
the job must be shared with the service principal, or Make will not see it in the list.
Databricks4

Get a job run output

ActionIn the docs only

Collects what a job run produced and hands it to the rest of the scenario, so you can alert a team, store the result or branch on it without opening Databricks.

When to use it
placed after Run a job, when someone downstream needs to know how the run went.
Watch out
each call is one operation, so avoid wiring it into a loop that asks again and again.

Pipelines

1 module
Databricks5

Get a pipeline update status

ActionIn the docs only

Tells your scenario where a pipeline update stands, which lets Make decide what comes next: warn the data owner, hold a report, or carry on with the rest of the flow.

When to use it
a dashboard or export depends on a pipeline and should only go out once its update is known.
Watch out
the service principal also needs permission on the pipeline itself, not only on the workspace.

Files

1 module
Databricks6

Upload a file to a Unity Catalog volume

ActionIn the docs only

Drops a file coming from another app into a Unity Catalog volume, so exports, attachments or partner files end up where your Databricks tables and notebooks can use them.

When to use it
a supplier sends a CSV by email or to a shared drive and it should reach Databricks untouched.
Watch out
grant the service principal access to the target volume before the first test run.
Need help

Need help automating Databricks with Make?

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FAQ

Databricks and Make: frequent questions

01Is the Databricks Make integration free?
No. The Databricks app is reserved to the Make Enterprise plan, so the Free plan and the other paid plans cannot use it. The Free plan does give access to 3,000+ standard apps, with 2 active scenarios and a 15 minute minimum interval, but enterprise apps such as Databricks sit outside it. You also need your own Databricks account with a service principal. Make counts each module execution as one operation against your plan.
02What does the Databricks Make connection require?
You need a Databricks account with a service principal, plus three values from it: the workspace URL copied from your browser, the Application ID used as Client ID, and an OAuth secret used as Client secret. You find the last two under Settings, Identity and access, Service principals. In Make, click Create a connection on any Databricks module, paste the three values and save. The service principal must also hold permissions on every job, pipeline, catalog or volume you plan to use.
03Does the Databricks Make integration react in real time?
It depends on what starts your scenario, because Databricks has no trigger module in Make. The flow begins either with a trigger from another app, which can be instant when that app calls Make through a webhook, or with a schedule on the first module. A new scenario is scheduled every 15 minutes by default, and paid plans can go down to one minute. The Databricks modules then act as soon as the scenario reaches them.
04What if a Databricks module is missing in Make?
The Databricks app offers 6 modules and has no Make an API Call module, so you cannot reach other parts of the Databricks API from this app. First check that the service principal has permission on the resource, since a job or volume it cannot see looks like a missing feature. If the gap is real, work around it with another app in the same scenario, or ask the team behind our Make agency to look at your case.
05Make or n8n for Databricks: which one fits?
Both can work, and the right choice depends on your setup rather than on the app. Databricks exists as an app in Make and as a node in n8n. On Make, it requires the Enterprise plan and offers 6 action modules around SQL, jobs, pipelines and files. If your company already runs on Make Enterprise, staying there keeps every connection in one place. If you are weighing both tools, compare them on the plans you have access to and the modules you need.
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