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Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT



GitHub connector details
The GitHub connector continuously captures repository and organization data from GitHub into Estuary collections using the GitHub REST API, enabling right-time visibility across code, collaboration, and DevOps activities.
- Comprehensive coverage: Captures a wide range of GitHub resources including commits, pull requests, issues, workflows, releases, stargazers, and more, spanning both batch and incremental data.
- Right-time synchronization: Continuously ingests new commits, issues, and discussions as they occur, providing developers and data teams with an up-to-date view of repository activity.
- Flexible authentication: Supports OAuth2 for secure browser-based access or Personal Access Tokens (PATs) for command-line or managed integration setups.
- Granular configuration: Allows selective repository capture, branch-level filtering, and adjustable page sizes for large projects.
- Scalable for enterprise teams: Efficiently handles multi-repository or organization-wide synchronization while respecting GitHub API rate limits.
- Schema-aligned structure: Each GitHub resource maps to a separate Flow collection, simplifying downstream analysis, metrics tracking, or data lake ingestion.
💡 Tip: For organizations with many repositories, use wildcard patterns (like org/*
) to automatically capture all repositories under one organization, ensuring comprehensive and future-proof coverage of your GitHub data.


HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes from GitHub in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your GitHub insights always reflect the latest data by connecting your databases to GitHub with change data capture.
- Or connect critical SaaS apps to GitHub with real-time data pipelines.
Don't see a connector?Request and our team will get back to you in 24 hours
Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
---|---|---|---|---|
Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
Speed | <100ms | 5min+ | Varies | <100ms |
Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
Scale |

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