Sync data from GitLab to Microsoft SQL Server

CloudQuery is the simple, fast data integration platform that can fetch your data from GitLab APIs and load it into Microsoft SQL Server

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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 GitLab to Microsoft SQL Server

Fast and reliable

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

Easy to use, easy to maintain

GitLab 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

Microsoft SQL Server isn’t the only place we can sync your GitLab data to. Whatever you need to do with your GitLab 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 GitLab to Microsoft SQL Server

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 GitLab to Microsoft SQL Server:

cloudquery init --source=gitlab --destination=mssql

This will generate a config file named gitlab_to_mssql.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 gitlab_to_mssql.yaml

This will start syncing data from the GitLab API to your Microsoft SQL Server 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.

How do I authenticate with GitLab to set up my sync to Microsoft SQL Server?

By default, the GitLab CloudQuery integration uses API Key authentication. If you want to use another method of authentication, you can specify this in the auth_method field. At present, the CloudQuery GitLab integration supports the bearer token and API key authentication methods. Both of these will require specific additional configuration parameters to be used. Full details can be found in the CloudQuery authentication documentation.

What information can I sync from GitLab to Microsoft SQL Server using CloudQuery?

The CloudQuery GitLab integration supports a variety of tables include project releases, branches, members and push rules. A full list of tables supported by the CloudQuery GitLab integration can be found in the tables documentation.

How can I protect my credentials when authenticating with Microsoft SQL Server?

For testing purposes, you can specify your username and password directly into the configuration file. However, we strongly recommend that you do not do this in a production environment as it could compromise the security of your credentials. In production, you should use environment variable substitution to keep your information secure.

What versions of MS SQL Server can I sync to from GitLab using CloudQuery?

The CloudQuery Microsoft SQL Server integration supports Microsoft SQL Server 2019 or later and Azure SQL Database version 2019 or later.