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.
No credit card required. Upgrade whenever you want.
Trusted by great companies
Move data in a few clicks
Connect your source
Authenticate your account and you're done. 100+ ready-made connectors, no code required.
Configure the sync
Pick the tables, the schedule and the update type: batch, cursor-based incremental or CDC.
Choose your destination
Load into BigQuery, Redshift, Databricks, PostgreSQL, ClickHouse, Amazon S3 and more.
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.
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.
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.
Learn moreComplete 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.
Learn moreEnd-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.
Learn moreBuilding data-driven stories
“Every new source implementation, if I had to do it myself, would take about two or three months. With Erathos, it's done in a few hours. I don't need the skills of a data engineer to generate real value from the company's data.”
“Erathos revolutionized data management at WE. By integrating multiple SaaS tools into a single DW, our technical team now focuses on the core business. We implemented dashboards with insights across every area, enriching our organizational culture and improving our decision-making.”
“We used to have a lot of rework, and now we don't. It's more efficient to work this way. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.”
“If I didn't have this infrastructure, I'd need three or four people to do what Erathos does today. I was able to generate real value from my data with a much leaner setup than I thought I'd need. That's the core of building a data-driven culture: the team only uses data when they can trust it.”
“Erathos brought a practical turnaround at CCM. We were able to integrate financial systems, CRM, and processes with BigQuery in just a few clicks, with no technical team required. That gave us a reliable data warehouse that powers automations, dashboards, and even our customer service bots.”
“The robustness and efficiency of Erathos's connectors — whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul — make the whole process much faster and more reliable. The technical documentation is extremely well put together and intuitive, which makes implementation much easier.”
Other paths for your data
Other destinations for GitHub
Other sources that land in BigQuery
CRMs, ERPs, ad platforms and databases, all through the same managed pipeline.
Frequently Asked Questions
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.
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.
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.
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.
Yes. Every Erathos connector includes a 14-day free trial. Connect GitHub to BigQuery and start syncing immediately—no credit card required.