# GitHub + BigQuery

> Sync repositories, pull requests, issues, commits, and GitHub members to BigQuery with Erathos. Incremental, no-code pipeline. Start free for 14 days.

Source: https://www.erathos.com/en/pipelines/github-bigquery
Em português: https://www.erathos.com/pipelines/github-bigquery

GitHub is a platform for developers that enables creation, hosting, and collaboration for code repositories, with version control via Git. Snowflake is a cloud-based data platform for storage, integration, and analytics, offering scalability, flexibility, and cost efficiency.

With Erathos, GitHub data lands in BigQuery in minutes, ready to be joined with other business sources in ad hoc queries, without your team having to manage ingestion infrastructure.

### What GitHub data does Erathos sync with Snowflake?

The integration automatically syncs the main GitHub objects:

- **Core entities**: automatically synced objects and records
- **Custom fields**: personalized properties included in the sync
- **Historical data**: complete initial load and incremental updates

### Why sync GitHub with BigQuery?

In BigQuery, you can join GitHub data with other business sources, running ad hoc queries in seconds over large volumes without managing infrastructure.

### How it works

Erathos connects to GitHub via 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. Every run is logged with full observability: runtime, processed rows, contextual errors, and instant alerts via Slack or email if anything goes wrong.

## Data in your data warehouse in minutes

### 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.

## 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.

## 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.