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Sync data from GitHub to PostgreSQL
CloudQuery is the simple, fast data integration platform that can fetch your data from GitHub APIs and load it into PostgreSQL
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Step by step guide for how to export data from GitHub to PostgreSQL
Table of Contents
MacOS Setup
Step 1: Install CloudQuery
To install CloudQuery, run the following command in your terminal:
brew install cloudquery/tap/cloudqueryStep 2: Create a Configuration File
Next, run the following command to initialize a sync configuration file for GitHub to PostgreSQL:
cloudquery init --source=github --destination=postgresqlThis will generate a config file named github_to_postgresql.yaml. Follow the instructions to fill out the necessary fields to authenticate against your own environment.
Step 3: Log in to CloudQuery CLI
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 loginStep 4: Run a Sync
cloudquery sync github_to_postgresql.yamlThis will start syncing data from the GitHub API to your PostgreSQL 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 PostgreSQL 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 PostgreSQL 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 PostgreSQL?
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 PostgreSQL?
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.Which database versions are supported?
The CloudQuery PostgreSQL integration supports syncing to PostgreSQL version 10 or higher and CockroachDB version 20.2 or higher.
How long will the sync take?
Sync duration depends on several factors, but there are a number of CloudQuery features that ensure that syncs are as fast as possible. CloudQuery syncs data from GitHub to PostgreSQL in a streaming fashion using Apache Arrow. This means that as soon as it receives data from GitHub it delivers it to the PostgreSQL integration. This means that data is delivered as the sync progresses rather than only at the end.
Can I send data to multiple PostgreSQL instances using the destination plug-in?
Yes, you can configure multiple destination blocks for different PostgreSQL instances or databases.
What are the best practices for handling large datasets with the PostgreSQL destination integration?
Use indexing, partitioning, and batch inserts to manage large datasets effectively and minimize performance impacts.
How do I monitor and troubleshoot data transfers to PostgreSQL?
Check CloudQuery logs for detailed error messages, validate connectivity settings, and monitor database performance using PostgreSQL’s built-in tools.