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GitHub BigQuery

Connect GitHub to BigQuery

Send GitHub issues, projects, users and 36 more data types to BigQuery on a schedule. Filter by date. Refresh as often as every 15 minutes.

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BigQuery dataset github
  • issues
  • projects
  • users
  • issue_timeline_events
  • assignees
  • 34 more data types
Each GitHub data type lands in its own table. You pick the dataset and table names.
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How to connect GitHub and BigQuery

5 steps. You can preview the GitHub data in Coupler.io before anything reaches BigQuery.

Step 1 of 5

Connect GitHub

Sign in to GitHub and authorize Coupler.io. There's no API key to copy.

Sign in with GitHub

Step 2 of 5

Choose what to export

Pick the GitHub data you want in BigQuery.

Show 31 more data types Show fewer data types
RepositoriesNot setSpecify GitHub repositories to export. Use org/repo format, org/* for all organization repositories.

Step 3 of 5

Fine-tune the export

Optional settings for this GitHub export.

Start dateAny dateSpecify the earliest date to begin exporting data from GitHub.
BranchesNot setSpecify repository branches to export commits from. Use org/repo/branch format.
API URLNot setSpecify the base URL for self-hosted GitHub Enterprise instances. Leave https://api.github.com/ for GitHub.com.
Max waiting time (minutes)Not setSpecify maximum time to wait when rate limits are reached before continuing the export.

Step 4 of 5

Connect BigQuery

Upload the JSON key file from your Google Cloud service account, then enter the dataset and table for the GitHub data.

JSON key filecoupler-service-account.jsonKey file from a GCP service account
Dataset namegithubExactly as it appears in BigQuery
Table nameissuesExisting table or a new name to create
Autodetect table schemaOnOn by default. Turn off to define the schema as JSON

Step 5 of 5

Choose a write mode and schedule

Every run either replaces or appends the data in BigQuery. Run it as often as every 15 minutes.

Write mode

Each run overwrites issues with fresh GitHub data.

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Get the most of GitHub to BigQuery integration

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Automate data

Access data that is always up to date by enabling the automatic data refresh on a schedule as often as every 15 minutes and using triggered automation.
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GitHub to BigQuery questions

39 data types, including Issues, Projects, Users, Issue timeline events and Assignees.

You sign in to GitHub and authorize Coupler.io. There's no API key to copy.

Yes. Set the start date to cover the period you need.

Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with GitHub data.

Refresh the source field list in Coupler.io and select the new column. If you define the BigQuery table schema manually, add the column there too.

On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.

Yes. Add more sources to the same data flow, for example ClickUp or Airtable, and join or append them before the data reaches BigQuery.

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