Google BigQuery data source PREVIEW release

Hi AppSheet Community,

I’m very excited to announce PREVIEW availability of the Google BigQuery data source. Please read the attached PDF Using the BigQuery Datasource - Preview User Guide.pdf (1.6 MB) for all the details, including licensing requirements (Enterprise plans required), Limitations (like Read-only and 100K rows max), and a full set of instructions with screenshots for getting your first BigQuery dataset added as an AppSheet table, including how to create a Google Cloud Service Account and Key.

This is a PREVIEW release, so please do not use this data source for production use cases. We will announce GA in 2-3 months after we have user feedback and have fixed any reported issues.

Where do I find the BigQuery data source?

Go to “My Account” / “My Account” / and select the “Sources” tab. You can add a new data source of type “Cloud Database”. When you click on the dropdown selection, you will see “BigQuery” as a new type of cloud database to choose from. Please follow the instructions in the PDF to get the required inputs to authenticate. If you don’t see it yet, please check back soon, it should be rolling out to all users today.

Please feel free to send us your use cases! I would love to hear about what you plan to do with BigQuery data in your AppSheet apps or automations. You can fill out this Google Form with your information!

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Might not really be a question for Appsheet, but what benefits would there be in using BigQuery instead of say a normal cloud MySQL database with 100k rows? Apart from someone that already uses BigQuery. Or is this just an expansion of feature set? I mostly ask cause it would be a google to google interaction.

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Hi @Austin_Lambeth ,

It would be primarily for folks who are already using BigQuery. In a lot of cases, there are already feeds coming from applications to BigQuery to support the business reporting use case, potentially from 10, 20 or even 50 applications. If any of that data is helpful to have in an AppSheet app as reference data to assist in filling in data gaps.

Let us say you have a product ID and name in your app backed by a sheet, but none of the product details like weight, dimensions, color, etc, because that information is locked away in an on-premises legacy application. However, there is already a nightly extract that is loading that into BigQuery. Now you can tap into that product database in BigQuery and use those additional attributes to make your sheets based app richer. And, you don’t have to create a new CloudSQL DB and figure out how to also extract and keep the info up to date in the CloudSQL DB.

Technically, if you have the ability to have the data in CloudSQL or in BigQuery, you can accomplish the same thing (given you can whiltelist access to CloudSQL, etc…), but it will require more DBA skills to do the CloudSQL route.