Question 1

How do I get a Databricks table into a spreadsheet?

Accepted Answer

Build a model on the Databricks connection, either by choosing a catalog, schema and table or by writing custom SQL, then point it at a spreadsheet and tab. Replace clears the data rows and writes the current result, keeping frozen header rows intact. Append starts after the last row with content. Set a schedule and the tab stays current without anyone running a query and pasting output into a shared file.

Question 2

Can I use a query I already have?

Accepted Answer

Yes, and it is how most people start. Custom SQL is wrapped as a subquery by Polytomic and run against your SQL warehouse, so an analyst with a query they trust can paste it in rather than rebuilding the logic somewhere new. Worth remembering the query runs on every scheduled sync, so if it is expensive, look at what it scans before choosing an aggressive schedule.

Question 3

Can specific rows be updated rather than replaced?

Accepted Answer

No. There is no key based update in place for Google Sheets, so a row cannot be matched and edited while leaving its neighbours alone. The pattern that works is letting Polytomic own a raw data tab using replace, then building the formulas, pivots and charts people actually look at on separate tabs that reference it. A refresh then never disturbs anybody's work.

Question 4

How much data fits before the sheet breaks?

Accepted Answer

Google caps a spreadsheet at 10 million cells, so the practical limit is that number divided by your column count, putting a twenty column model at roughly 500,000 rows. Cells are also cut off at 50,000 characters. If a model is close to either figure the sheet should probably hold an aggregate, with the detail staying in Databricks where it can actually be queried.

Question 5

Who is this actually for?

Accepted Answer

The people who will never open a notebook, which in most companies is finance and operations. They work in spreadsheets, and telling them to learn something else rarely works. Reverse ETL meets them where they are while keeping the numbers tied to a model the data team maintains, so the definitions match reporting instead of drifting the moment somebody downloads a file and starts editing their own copy.

Sync Databricks to Google Sheets

Sync Databricks to Google Sheets with Polytomic

Table or custom SQL

Replace or append

Mind the cell ceiling

Or sync Google Sheets to Databricks

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Step-by-step integration guide

Connect Databricks in Polytomic

Connect Google Sheets in Polytomic

Create a sync between Databricks and Google Sheets

Map fields and enable the sync

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