GitHub + BigQuery
GitHub is the world’s leading platform for code hosting, Git-based version control, and software development collaboration. Engineering teams centralize repositories, pull requests, code review, issues, and org member activity in GitHub, making it the largest source of data on software throughput, quality, and productivity.
In practice, GitHub acts as the operating system for software delivery: from commit to merge, from bug report to closed issue, every engineering productivity signal is captured there, ready to be joined with product, support, and business data in a data warehouse.
With Erathos, you can integrate GitHub data into BigQuery in minutes. Our platform handles the entire data movement process into your analytics environment and lets you combine this data with other sources in your Data Warehouse. That way, your time goes to what really creates value — extracting actionable insights and making more data-driven decisions.
Which GitHub data does Erathos sync with BigQuery?
The integration automatically syncs GitHub’s main objects:
Repositories — name, organization, language, default branch, issue count, and activity dates
Pull requests — author, reviewers, status, open, close, and merge dates
Issues — author, assignees, labels, status, milestone, and dates
Commits — author, message, date, and repository
Org members — users, login, roles, and membership dates
Why sync GitHub with BigQuery?
In BigQuery, you can combine engineering data with product, revenue, and support — operationalizing DORA metrics, calculating PR lead time by team, identifying systemic review bottlenecks, and correlating delivery speed with customer retention.
How it works
Erathos connects to GitHub via the official API and syncs your data incrementally — only new or updated records are processed in each run, keeping pipelines fast and BigQuery costs predictable. You choose the sync frequency (from 5 minutes to daily), the objects to sync, and the destination dataset. Each run is logged with full observability: execution time, rows processed, errors with context, and instant alerts via Slack or email if anything goes wrong.
No credit card required.
Why do data teams choose Erathos for GitHub?
GitHub connector ready to use
Connect GitHub to BigQuery and automatically export repositories, pull requests, issues, commits, and org members. Centralized engineering data to power DORA metrics and engineering analytics — no CSVs, no scripts.
Complete control over your GitHub pipelines
Configure schedule, frequency, and sync type at the table level. Incremental synchronization processes only new or modified records—keeping BigQuery costs low and your analyses always up to date.
End-to-end observability
Stop finding out about GitHub failures only after the business team complains. Every run is logged with runtime, rows processed, and error context. Get automatic alerts via Slack, Discord, or email as soon as anything goes off track — so your data stays up to date and ready for analysis.
Why Companies Move GitHub Data to BigQuery with Erathos
Centralizing GitHub data in BigQuery has never been this simple
Erathos is a data ingestion platform for data teams. With the GitHub connector, you can automatically export repositories, pull requests, issues, commits, and org members to BigQuery — centralizing engineering data and making it ready to track DORA metrics, measure review bottlenecks, and provide audit-ready control evidence.
Our Customers
Trusted by data-driven companies
Simplified data ingestion
1
Select your data source
More than 80 plug-and-play connectors to consolidate data from multiple sources, eliminate time-consuming manual processes, and create a streamlined path forward.
2
Setup your pipeline
Manage your pipeline seemlessly. Select a sync hour, frequency and type at a table/endpoint level.
3
Select your data warehouse
Choose between Amazon S3, BigQuery, Databricks, Redshift and PosgreSQL to centrlize your data
FAQ
What is Erathos and how can it help my company?
Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect tools like GitHub to their data warehouse—with full observability into every run, zero maintenance, and none of the opacity found in traditional market tools.
What GitHub data does Erathos sync to BigQuery?
Erathos syncs GitHub repositories, pull requests, issues, commits, and organization members into BigQuery. Ready-to-use data to track DORA metrics, measure PR lead time, identify review bottlenecks, and surface access controls for auditing.
How often does Erathos synchronize data from GitHub to BigQuery?
You can configure synchronization frequency from every 5 minutes up to daily, at the table level. Erathos uses incremental synchronization—only new or updated records are processed in each run, keeping the GitHub pipeline efficient and BigQuery costs predictable.
What happens if a GitHub sync fails?
Erathos automatically detects failures and sends alerts to your email, Slack, or Discord with full context—not just "job failed." Smart retries handle transient errors, and every execution is logged with run time, processed rows, and error context so your team can debug in minutes, not hours.
Is there a free trial period for the GitHub connector?
Yes. Every Erathos connector includes a 14-day free trial. Connect GitHub to BigQuery and start syncing immediately—no credit card required.