Modern businesses are slowly moving away from the traditional database management systems to technologically advanced ones, more specifically to platforms operating in the cloud. One of the most optimized ways of doing so is to migrate databases from Microsoft SQL Server to Snowflake. 

Why should organizations decide on this type of data migration to optimize operating efficiencies?

Benefits of Snowflake

Here are some of the main benefits of Snowflake that make migrating databases from SQL Server to Snowflake a win-win proposition for businesses. 

Snowflake is a cloud-based data warehousing platform. It is based on either Amazon Web Services (AWS) or Microsoft Azure. Several benefits are offered by Snowflake when compared to traditional databases such as SQL Server.  

• Snowflake supports several cloud vendors and hence users can work on any of them with the same set of tools and knowledgebase. 

• Data in native form – unstructured, semi-structured, or structured – can be loaded into Snowflake. This feature is not offered by leading traditional databases such as SQL Server or Oracle.

• Snowflake offers excellent computing speeds without any drop in database performance. 

• Snowflake offers computing and storage facilities that can be distinguished from one another.   

• There is no limit on the quantum of storage facility for users. Additional storage can be downloaded on demand any time. 

• One of the critical benefits of Snowflake is that it offers all-inclusive services from automatically clustering data without defining indexes to the encoding of columns. For very large tables, users may avail the option of co-locating data through cluster keys. 

How to Move Databases From SQL Server to Snowflake

There are four stages in the process to migrate databases from SQL Server to Snowflake.

• Extract data from the SQL server through queries for extraction. The data is sorted and filtered through select statements before it is mined. 

• The extracted data must be processed and formatted to match the data architecture that is supported by Snowflake. However, it is not necessary to specify a schema beforehand for loading JSON or XML data.

• Even after the data is processed and formatted, it cannot be loaded directly into Snowflake but must be kept in an internal or external staging area. 

• An internal staging area is created by users with SQL statements and a name and type of file format are allotted to it. Microsoft Azure and Amazon Simple Storage Service S3 are Snowflake-supported external staging areas.  

• The final step in SQL Server to Snowflake database migration is to transfer data from the staging area to Snowflake. Use the Data Loading Overview tool for large databases and the data loading wizard of Snowflake for smaller ones. is ideal. The PUT command is used to stage files for bulk databases and the COPY INTO command is used to load the processed data into an intended table in Snowflake.

This is how to move databases from SQL Server to Snowflake.