How to load data from GitHub to Convex

Learn how to use Airbyte to synchronize your GitHub data into Convex within minutes.

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Set up a GitHub connector in Airbyte

Connect to GitHub or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Convex for your extracted GitHub data

Select Convex where you want to import data from your GitHub source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the GitHub to Convex in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up GitHub as a source connector (using Auth, or usually an API key)
set up Convex as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is GitHub

GitHub is a renowned and respected development platform that provides code hosting services to developers for building software for both open source and private projects. It is a heavily trafficked platform where users can store and share code repositories and obtain support, advice, and help from known and unknown contributors. Three features in particular—pull request, fork, and merge—have made GitHub a powerful ally for developers and earned it a place as a (developers’) household name.

What is Convex

Convex is a platform that provides a suite of tools for building and deploying machine learning models. It offers a user-friendly interface for data scientists and developers to create and train models, as well as a scalable infrastructure for deploying them in production. Convex also includes features such as automated model tuning, version control, and collaboration tools to streamline the machine learning workflow. The platform is designed to be flexible and customizable, allowing users to integrate their own libraries and frameworks. Overall, Convex aims to simplify the process of building and deploying machine learning models, making it accessible to a wider range of users.

Integrate GitHub with Convex in minutes

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Prerequisites

A GitHub account to transfer your customer data automatically from.
A Convex account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including GitHub and Convex, for seamless data migration.

When using Airbyte to move data from GitHub to Convex, it extracts data from GitHub using the source connector, converts it into a format Convex can ingest using the provided schema, and then loads it into Convex via the destination connector. This allows businesses to leverage their GitHub data for advanced analytics and insights within Convex, simplifying the ETL process and saving significant time and resources.

Step 1: Set up GitHub as a source connector

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.

Step 2: Set up Convex as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. From there, click on the "Add Destination" button in the top right corner of the screen.
4. In the search bar, type "Convex" and select the Convex destination connector from the list of options.
5. Next, you will need to enter your Convex API key. This can be found in your Convex account settings.
6. Once you have entered your API key, click on the "Test" button to ensure that the connection is working properly.
7. If the test is successful, click on the "Save" button to save your settings.
8. You can now use the Convex destination connector to transfer data from Airbyte to your Convex account.

Step 3: Set up a connection to sync your GitHub data to Convex

Once you've successfully connected GitHub as a data source and Convex as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select GitHub from the dropdown list of your configured sources.
Select your destination: Choose Convex from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific GitHub objects you want to import data from towards Convex. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from GitHub to Convex according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Convex data warehouse is always up-to-date with your GitHub data.

Use Cases to transfer your GitHub data to Convex

Integrating data from GitHub to Convex provides several benefits. Here are a few use cases:

Advanced Analytics: Convex’s powerful data processing capabilities enable you to perform complex queries and data analysis on your GitHub data, extracting insights that wouldn't be possible within GitHub alone.
Data Consolidation: If you're using multiple other sources along with GitHub, syncing to Convex allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: GitHub has limits on historical data. Syncing data to Convex allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Convex provides robust data security features. Syncing GitHub data to Convex ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Convex can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding GitHub data.
Data Science and Machine Learning: By having GitHub data in Convex, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While GitHub provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Convex, providing more advanced business intelligence options. If you have a GitHub table that needs to be converted to a Convex table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a GitHub account as an Airbyte data source connector.
Configure Convex as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from GitHub to Convex after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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Step 1: Set up GitHub as a source connector

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."

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.

Step 2: Set up Convex as a destination connector

Step 3: Set up a connection to sync your GitHub data to Convex

Once you've successfully connected GitHub as a data source and Convex as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select GitHub from the dropdown list of your configured sources.
Select your destination: Choose Convex from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific GitHub objects you want to import data from towards Convex. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from GitHub to Convex according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Convex data warehouse is always up-to-date with your GitHub data.

How to Sync GitHub to Convex Manually

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FAQs

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 is GitHub?

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?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up GitHub to Convex as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from GitHub to Convex and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

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.

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Engineering Analytics

How to load data from GitHub to Convex

Learn how to use Airbyte to synchronize your GitHub data into Convex within minutes.

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Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between GitHub and Convex

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TL;DR

set up GitHub as a source connector (using Auth, or usually an API key)
set up Convex as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is GitHub