GitHub
Engineering Analytics
Sync GitHub data anywhere.
- Certified
- Generally available
- 39 streams
- 24 entities
- Read & write
- 39Streams
- 24Entities
- 7Actions
- 50+Destinations
Everything GitHub can do in Airbyte
Sync to your warehouse
Land 39 GitHub tables in 50+ destinations on a schedule you control.
Live entity actions
Read, create and update GitHub records at runtime through typed entity actions.
Context store search
Query synced GitHub data with filters, sorting and semantic search, without spending GitHub API rate limits.
Incremental syncs
Pull only the records that changed since the last run instead of reloading everything.
Sync capabilities
- Full Refresh SyncSupported
- Incremental SyncSupported
- Available onCloud, Self-Managed Enterprise
- Destinations50+ Airbyte connectors
- Connector version2.1.42
Set up in 7 steps
- Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
- Click on the "GitHub" source connector and select "Create a new connection."
- Enter a name for the connection and click "Next."
- Enter your GitHub credentials, including your username and personal access token. If you do not have a personal access token, you can create one by following the instructions provided in the Airbyte documentation.
- Select the repositories you want to connect to Airbyte and click "Test Connection" to ensure that the connection is successful.
- Once the connection is successful, click "Create Connection" to save the connection.
- You can now use the GitHub source connector to extract data from your selected repositories and integrate it with other data sources in Airbyte.
Every table you can sync from GitHub
Assignees
Branches
Contributor Activity
Collaborators
Issue labels
Organizations
Pull request commits
Tags
TeamMembers
TeamMemberships
Teams
Users
Supported GitHub actions
Get
Fetch a single record by ID.
List
Read live records straight from the GitHub API.
API Search
Context Store Search
Query synced data with filters and sorting, with no API rate limits.
Create
Write a new record back into GitHub.
Update
Patch fields on an existing record.
Semantic Search
Natural-language search across synced GitHub records.
Authenticate GitHub once
OAuth
RecommendedPersonal Access Token
What teams build with GitHub
Show me all open issues in my repositories this month
List the top 5 repositories I've starred recently
Analyze the commit trends in my main project over the last quarter
Find all pull requests created in the past two weeks
Search for repositories related to machine learning in my organizations
Compare the number of contributors across my different team projects
Common questions
Do I need more than one GitHub connection?
No. One GitHub authorization powers both the scheduled syncs that land data in your destination and the entity actions your agents call at runtime.
Do GitHub entity actions need a sync to run first?
No. Entity actions read and write through the GitHub API as they are called, so they work immediately. Context store search is the exception: it queries data Airbyte has already synced, which is what lets it filter and sort without spending API rate limits.
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
What data can you extract from GitHub?
GitHub's API provides access to a wide range of data related to repositories, users, organizations, and more. Some of the categories of data that can be accessed through the API include:
- Repositories: Information about repositories, including their name, description, owner, collaborators, issues, pull requests, and more.
- Users: Information about users, including their username, email address, name, location, followers, following, organizations, and more.
- Organizations: Information about organizations, including their name, description, members, repositories, teams, and more.
- Commits: Information about commits, including their SHA, author, committer, message, date, and more.
- Issues: Information about issues, including their title, description, labels, assignees, comments, and more.
- Pull requests: Information about pull requests, including their title, description, status, reviewers, comments, and more.
- Events: Information about events, including their type, actor, repository, date, and more.
Overall, the GitHub API provides a wealth of data that can be used to build powerful applications and tools for developers, businesses, and individuals.
How do I transfer data from GitHub?
1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "GitHub" source connector and select "Create a new connection."
3. Enter a name for the connection and click "Next."
4. Enter your GitHub credentials, including your username and personal access token. If you do not have a personal access token, you can create one by following the instructions provided in the Airbyte documentation.
5. Select the repositories you want to connect to Airbyte and click "Test Connection" to ensure that the connection is successful.
6. Once the connection is successful, click "Create Connection" to save the connection.
7. You can now use the GitHub source connector to extract data from your selected repositories and integrate it with other data sources in Airbyte.
What are top ETL tools to transfer data from GitHub?
The most prominent ETL tools to transfer data to include: Airbyte, Fivetran, StitchData, Matillion, Talend Data Integration. These tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into and other databases, data warehouses and data lakes, enhancing data management capabilities.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
Start moving GitHub data today
Free for 14 days on Airbyte Cloud. One connection powers your scheduled syncs and your live GitHub actions.