Sync data from GitHub to Databricks

CloudQuery is the simple, fast data integration platform that can fetch your data from GitHub APIs and load it into Databricks

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Self-hosted

Start locally, then deploy to a Virtual Machine, Kubernetes, or anywhere else. Full instructions on CLI setup are available in our documentation.

Step-by-step Instructions

Cloud-hosted

Start syncing in a few clicks. No need to deploy your own infrastructure.

Coming soon for GitHub to Databricks

Fast and reliable

CloudQuery’s efficient design means our syncs are fast and a sync from GitHub to Databricks can be completed in a fraction of the time compared to other tools.

Easy to use, easy to maintain

GitHub syncing using CloudQuery is easy to set up and maintain thanks to its simple YAML configuration. Once synced, you can use normal SQL queries to work with your data.

A huge library of supported destinations

Databricks isn’t the only place we can sync your GitHub data to. Whatever you need to do with your GitHub data, CloudQuery can make it happen. We support a huge range of destinations, customizable transformations for ETL, and we regularly release new plugins.

Extensible and Open Source SDK

Write your own connectors in any language by utilizing the CloudQuery open source SDK powered by Apache Arrow. Get out-of-the-box scheduling, rate-limiting, transformation, documentation and much more.

Step by step guide for how to export data from GitHub to Databricks

MacOS Windows Linux

MacOS Setup

Step 1: Install CloudQuery

To install CloudQuery, run the following command in your terminal:

brew install cloudquery/tap/cloudquery

Step 2: Create a Configuration File

Next, run the following command to initialize a sync configuration file for GitHub to Databricks:

cloudquery init --source=github --destination=databricks

This will generate a config file named github_to_databricks.yaml. Follow the instructions to fill out the necessary fields to authenticate against your own environment.

Next, log in to the CloudQuery CLI. If you have't already, you can sign up for a free account as part of this step:

cloudquery login

Step 4: Run a Sync

cloudquery sync github_to_databricks.yaml

This will start syncing data from the GitHub API to your Databricks database! 🚀

See the CloudQuery documentation portal for more deployment guides, options and further tips.

FAQs

What is CloudQuery?

CloudQuery is an open-source tool that helps you extract, transform, and load cloud asset data from various sources into databases for security, compliance, and visibility.

Why does CloudQuery require login?

Logging in allows CloudQuery to authenticate your access to the CloudQuery Hub and monitor usage for billing purposes. Data synced with CloudQuery remains private to your environment and is not shared with our servers or any third parties.

What data does CloudQuery have access to?

CloudQuery accesses only the metadata and configurations of your cloud resources that you specify without touching sensitive data or workloads.

How is CloudQuery priced?

CloudQuery offers flexible pricing based on the number of cloud accounts and usage. Visit our pricing page for detailed plans.

Is there a free version of CloudQuery?

Yes, CloudQuery offers a free plan that includes basic features, perfect for smaller teams or personal use. More details can be found on our pricing page.

What authentication methods does the CloudQuery GitHub integration support?

The CloudQuery GitHub integration supports two authentication methods and the best option for your sync to Databricks will depend on your personal preferences and your organizational security policy.

What is the difference between personal access tokens and app authentication?

The main difference your choice of authentication method will make to your sync from GitHub to Databricks is the rate at which CloudQuery can read and sync data. Personal access tokens have a lower rate limit than app authentication - so if you need to move a particularly large amount of data quickly, we would recommend using app authentication.

Which tables can I sync from GitHub to Databricks?

A full list of supported tables is available in the tables tab on our integration information page.

Will archived repos be included in the sync from GitHub to Databricks?

Archived repos will only be synced if a specific request is made. To include archived repos in the sync, include_archived_repos must be set to true.