The Why And How Of Migrating Databases From MS SQL Server to Snowflake

The modern business ecosystem is largely data-driven with organizations having to deal with massive amounts of data originating from both external and internal sources. This divergence from traditional manual work methodologies has resulted in increased organizational operating efficiencies. The power of data analytics has been tapped by businesses to make cutting-edge decisions in real-time to stay ahead of other competitors in the field.

In this form of environment, one thing stands out and that is businesses must ensure that their systems are capable of processing massive volumes of data without any lag or drop in performance. The most optimized way to do so is to migrate their conventional database systems to the cloud which offers several cutting-edge advantages.

This is the starting point of this post as we go into the intricacies of migrating databases from Microsoft SQL Server to Snowflake, a cloud-based platform.  

Before going into the several factors of why you should move databases from SQL Server to Snowflake and how to do so, a quick look at the two as individual entities will make you understand the process better. You will also know why migrating databases from SQL Server to Snowflake is so important today and taken up by most enterprises.

Before going into the migration process, let us check the working of the SQL Server Snowflake individually in isolation. It will help you to understand better why migrating databases from SQL Server to Snowflake is so important.

So, let us get started.

Microsoft SQL Server

Along with DB2 from IBM and Oracle, the Microsoft SQL Server is among the top database technologies in the world and is widely used. It is based on the SQL programming language and supports applications as a standalone system or on local area networks across the web, integrating fully into the whole Microsoft ecosystem.

The SQL Server is a Relational Database Management System (RDMS) and comes with the Microsoft .NET framework out of the box. Users can carry out a wide range of analytics and intricate queries on the SQL Server.


Snowflake is a cloud-based data warehousing platform that brings all the technologically advanced features of the cloud to the table. When compared to the SQL server, it is a comparatively new concept but within a short period has taken the world by storm. This has led to businesses preferring to migrate their databases from the SQL Server to Snowflake to take advantage of the features of the cloud.

Benefits Of Snowflake And Why You Should Migrate Databases To This Platform

There are several benefits of Snowflake that give it a head start when compared with the SQL Server.

# Snowflake offers separate storage and computing facilities, unlike traditional databases where the two are closely linked. Hence, with Snowflake, it is easy to estimate the costs of data usage individually. Further, as these are two separate entities, users can avail storage space, scale up and down as per their requirements, and pay only for the quantum used. This leads to substantial savings in IT infrastructure costs by organizations.

# Apart from unlimited storage space, Snowflake also offers high computing capabilities. Several users can simultaneously execute complex and intricate queries without a drop in performance.

All types of data whether it is unstructured, semi-structured, or structured can be migrated to Snowflake without first processing or formatting it. Snowflake provides in-built support to JSON, Avro, XML, and Parquet data.

# Since Snowflake is an automated cloud-based solution, there is no need to define indexes before clustering data. This feature is applicable both to computing and encoding of columns. However, users must use clustering keys manually to co-locate table data when the tables are very large.

# Snowflake is compatible with a wide range of cloud vendors and therefore, users do not have to learn how to handle new tools and technologies when working on databases migrated to this platform.

Due to these benefits on offer, it makes sense for organizations to migrate SQL Server to Snowflake and be on this cloud-based data warehousing platform.

How To Migrate Database From SQL Server To Snowflake

There are four steps involved in migrating databases from SQL Server to Snowflake.

Step 1

Extract data from the SQL Server through queries for extraction and select statements. These help in sorting, filtering, and limiting the data during the mining of the data. The Microsoft SQL Server Management tool automatically extracts the data for large databases in text, CSV, or SQL query formats.

Step 2   

The extracted data cannot be dumped into Snowflake at this stage, it must be processed and formatted to a data structure that is supported by Snowflake. However, this step is not required for XML or JSON data.

Step 3

The processed and formatted data cannot be moved directly to Snowflake but must be placed in a temporary location also known as a staging area. It might either be an internal or an external staging area.

An internal staging area is created by users with SQL statements while data can be uploaded directly to an external staging area. Presently, the external staging areas supported by Snowflake are MS Azure and Amazon Simple Storage Service (S3).

Step 4

The data that has been kept in a temporary staging area can now be migrated to Snowflake. Small databases can be migrated through the Snowflake data loading wizard. For moving large databases and bulk data, use the Data Loading Overview tool of Snowflake. The commands to be executed in this case are PUT to stage files and COPY INTO to load processed data into a particular table.

This completes the process of migrating databases from the SQL Server to Snowflake.

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