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SQL Server To Snowflake

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SQL Server To Snowflake

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  1. Steps to Migrate SQL Server Database to Snowflake

  2. Organizations are today globally opting to migrate their existing databases to more technologically advanced platforms to optimize their data management process. One of the most common processes being adopted today is migrating Microsoft SQL Server databases to Snowflake which is based entirely on the cloud. Before going into the finer details on steps to do so, an overview of both will be in order.

  3. Microsoft SQL Server Microsoft SQL Server is a combination of Relational Database Management System (RDMS) and Structured Query Language (SQL) mainly used for data storage and retrieval. While the data center version caters to large applications, a freeware version takes care of the lower end. The main advantage of SQL Server is that a single machine can run applications across the web or on a local area network.

  4. Snowflake Despite these features, businesses want to migrate databases from SQL Server to Snowflakebecause of the many inherent benefits of Snowflake. It is a cloud-based data warehousing solution offering almost unlimited storage and computing facilities. Users can scale up and down as per requirements, paying only for the quantum of resources used. Further, it is a high-performance platform and multiple users can execute multiple intricate queries simultaneously without any drop in performance.

  5. Steps for migrating SQL Server to Snowflake There are four steps in this process. It is not complicated as the tools for it are automated. · The first step is to extract data from SQL Server through queries for extraction by using select statements to sort, filter, and limit the data during extraction. For large databases in CSV, SQL queries, or text format, Microsoft SQL Server Management Studio is used. · This extracted data has to be processed and formatted before migration. Snowflake supports specific data types and the extracted data should match these data structures. A schema is not required for JSON or XML data before migration. · The processed and formatted data cannot be loaded directly into Snowflake but has to be kept in a temporary location. There are two parts here – external and internal stages. For external locations, Snowflake currently supports Microsoft Azure and Amazon S3. For the internal stage, it has to be created by the user with SQL statements and a name and format have to be assigned to the intended table. · The final step in SQL Server to Snowflakeprocessis loading the data staged in the temporary locations to Snowflake. For large databases, the COPY command is used while for small databases the data loading wizard of Snowflake is applied. While the migration of a database from SQL Server to Snowflakeis a one-time affair, it has to be ensured that all incremental changes and modifications to data are automatically carried out. Once done, full refreshes to the data need not be carried in the event of any changes made to data at the source.

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