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Migrating Database From Microsoft SQL Server to Snowflake

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Migrating Database From Microsoft SQL Server to Snowflake

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  1. Migrating Database From Microsoft SQL Server to Snowflake Before going into the process of migrating databases from SQL Server to Snowflake, it is necessary to understand why organizations want to do so and what are the benefits from it. 

  2. SQL Server is a database platform that integrates easily into the Microsoft ecosystem and backs the .NET framework out of the box. It is a relational database management system, is designed on the SQL programming language, and is ideal to query data in the databases.

  3. Snowflake is a cloud-based data warehousing solution compatible with several cloud vendors. All types of data like unstructured, semi-structured, and structured in their native formats can be loaded into Snowflake. This feature is not available either in Microsoft SQL Server or Oracle database and is a critical reason for migrating databases from SQL Server to Snowflake.

  4. There are several benefits of Snowflake.9 • The platform has high computing capabilities with no drop in speeds and performance even when multiple users simultaneously execute intricate queries. Snowflake has separate computing and storage facilities and users can scale up or down in either of them by paying only for the quantum of resources used. Hence, by moving from SQL Server to Snowflake, organizations can save substantially on IT infrastructure maintenance costs.

  5. The advantage of being a cloud-based platform is that Snowflake offers unlimited storage and computing capabilities. Businesses, therefore, do not have to invest in additional hardware and software whenever there is a spike in demand for resources. Finally, users of Snowflake get comprehensive packaged services from encoding of columns to automatic clustering of data without defining indexes.  • For migrating databases from SQL Server to Snowflake, there are four steps. 

  6. First, the data has to be extracted from the Microsoft SQL Server through queries for extraction. For bulk data extraction and full databases in CSV, SQL queries, or text format, the built-in SQL Server Management Studio tool is used. • The second step is formatting the extracted data before loading it into Snowflake. This is because the data structure has to match those that are supported by Snowflake. However, this formatting is not required when migrating XML or JSON data into Snowflake. 

  7. Even after the data is formatted and processed, it cannot be loaded into Snowflake. The third stage is parking the data in an internal or external staging area. An internal location has to be created by the user with SQL statements and a name and file type allotted to it. For the external stage, Snowflake presently supports Amazon S3 and Microsoft Azure. • The data in the staging area can now be loaded into Snowflake and is the fourth and final step in database migration from SQL Server to Snowflake. For large databases, the Data Loading Overview tool of Snowflake guides users through the process. For small databases, the data loading wizard of Snowflake is ideal. • This is the database migration process from SQL Server to Snowflake.

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