Firestore to Google Data Studio

Automatically Export & Sync Firestore Data to Google Data Studio

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Google Data Studio
Full data sets
No code
No complicated flow charts
No triggers
Set up in under 3 minutes
No instructions needed

Data sets

Uniform JSON Objects
Varied JSON Objects

Built for Synchronization

This service is designed to help anyone continuously export (i.e. "sync") data from Firestore.

If you only need to export your data one time, check the website of Firestore to see if their service offers a one-time export feature natively. Sometimes a Data Source's native export feature may provide not as much data as its API does, in which case Flatly is the solution.

Additional Information

Flatly uses official API channels to provide an integration with Firestore.
Cloud Firestore is a flexible, scalable database for mobile, web, and server development from Firebase and Google Cloud.

There are no scripts, downloads or extensions required for this integration. Flatly uses Service Account authorization for Firestore. Bring your own Service Account key and then simply enter a path to your Collection.

Project Data versus Database Data

Flatly syncs Firestore Database data, namely the contents of Documents in specific Collections. It does not sync Project Data like Crashlytics or A/B Testing. Behind the scenes the service first converts Firestore Documents to JSON and then efficiently flattens that JSON into flat files for spreadsheets or storage, or newline JSON for BigQuery.

Data Volume

If you expect your Firestore Collection to contain more than 10 million cells worth of data, do not attempt to sync Firestore to Google Sheets, as Google Sheets is limited to 10 million cells. Instead, use any cloud storage or BigQuery.


Flatly's access to Plaid and Plaid's downstream connected financial institutions is read-only access to text. It is limited to account data (words, numbers, dates). It does not include any money-movement, transfer capabilities or account holder profiles/identities.

Plaid alone interfaces directly with financial institutions, caches data from those institutions on Plaid infrastructure, and then makes the appropriate scoped subset of that data available to partners like Flatly using secure connections called client libraries.


Opening a CSV file from Google Cloud Storage in Looker Studio is straightforward and takes only a few clicks. Importantly, a CSV file can be larger than 10 million cells, whereas a Google Sheet is limited to 10 million cells.

Google Data Studio reads flat files directly from Google Sheets or Google Cloud Storage.

File Formats

Integration Flow


Step 1

Select Firestore from the Data Source dropdown and Google Data Studio from the Data Destination dropdown.

Step 2

Authorize Firestore with your credentials using the Service Account flow.

Step 3

Authorize Google Data Studio with your credentials using the Service Account flow.

Step 4

Select your Data Set from the 2 Data Sets available using the dropdown.

Step 5

Click Flatten to sync your data.

Walkthrough Video

Extended Data Sources

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