How to combine data from Snowflake with Microsoft SQL Server

Pipes allows you to quickly Integrate Snowflake with Microsoft SQL Server data for a combined analysis.
Load data from Snowflake and Microsoft SQL Server into your central data warehouse to analyze it with the business intelligence tool of your choice.
Pipes allows you to connect to Snowflake, Microsoft SQL Server, and more than 200 other APIs, web services, and databases with ready-to-use data connectors. Automate your data workflows through data pipelines without a single line of code.
1

Connect your data warehouse

It will be the destination of all data pipelines you build. Pipes supports relational databases in the cloud and on-premises.
2

Connect to Snowflake and Microsoft SQL Server

You just need to enter the associated credentials to allow Pipes access to the Snowflake API and the Microsoft SQL Server API.
3

Combine data from Snowflake and Microsoft SQL Server

Pipes lets you select the data from Snowflake and Microsoft SQL Server that you want to load to your data warehouse. These data pipelines will run automatically on your defined schedule!

About Snowflake

Snowflake is a high performing cloud data warehouse. It can either be used to store your data in it or / and to use it as a data source.

About Microsoft SQL Server

Microsoft SQL Server is a popular relational database management system. As a database server Microsoft SQL Server stores and retrieves data which may run either on another computer across a network or on the same computer, requested by other software applications.

Your benefits with Pipes

Get central access to all your data

Access data from 200+ data sources with our ready-to-use connectors and replicate it to your central data warehouse.

Automate your data workflows

Stop manually extracting data and automate your data integration without any coding. We maintain all pipelines for you and cover all API changes!

Enable data-driven decision-making

Empower everyone in your company with consistent and standardized data, automate data delivery and measure KPIs across different systems.