Import your Gitlab data to MS SQL Server

Import your data from Gitlab to MS SQL Server - Blendo.co

Easily ETL your Gitlab data into MS SQL Server

With Blendo Gitlab integration, it is easy to import Gitlab data into MS SQL Server to get more answers about your issues, development projects and releases. Drill down to your development teams’ data measure their efficiency. Combine it with data from customer support and customer success and see if your converted users are actually creating value or how response and development time of a support ticket affect your customers.

Use Cases

As soon as your Gitlab data is synced into MS SQL Server here are some ways you can use it.

MEASURING TEAM PERFORMANCE

See the progress of your tickets and time of resolution.

CUSTOMER SUPPORT ROI

Find out if your development efforts bring the return you expect. Combine it with data from billing and uncover your ROI.

AD CAMPAIGN CONVERSION

Combine data from other sources like support and sales. Uncover what features and development effort converted more valuable users.

How to get started with Gitlab and MS SQL Server data integration

Loading your Gitlab data into MS SQL Server is easy. First, you need to connect MS SQL Server as a Destination data warehouse. Then add Gitlab as a Data Source. It will take three minutes to set it up. Next, Blendo will import any information from Gitlab and load it into your MS SQL Server data warehouse. We do the heavy lifting so you can drill down to your data with your issues, development projects and releases.

Connect MS SQL Server

Connect MS SQL Server

Connect Gitlab as Data Source

Connect Gitlab as Data Source

We will load all your Gitlab data

We will load all your Gitlab data

Read more on how you can use your Gitlab data after you have them in your data warehouse.

Detailed Documentation

Check our documentation on how to setup Gitlab integration as a Data Source and start syncing your development data to MS SQL Server.

Check our documentation on how to connect MS SQL Server as a Data warehouse destination and start loading your data in minutes.