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SQL Server To Snowflake

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SQL Server To Snowflake

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  1. Migrating SQL Server Database to Snowflake

  2. Many organizations around the world are now opting to migrate databases from their existing platforms to technologically advanced cloud-based systems. It not only makes database management easy but also automates most processes.  One method that is common today is migrating databases from SQL Server to Snowflake.Microsoft SQL Server is a Relational Database Management System (RDMS) for data retrieving and storage. Applications are either supported on a local area network or across the web on a single machine. SQL Server integrates seamlessly with the full Microsoft ecosystem. 

  3. Snowflake is a cloud-based data warehousing solution with several cutting-edge and optimized features. For one, it allows the migration of both structured and unstructured data. Being cloud-based, it provides almost unlimited storage and computing powers with users able to scale up and down as per requirements, by paying only for the quantum of resources used. Snowflake is a high performing platform. There is no drop or lag even when several users simultaneously execute intricate queries. Hence it makes sense to migrate databases from SQL Server to Snowflake.  

  4. The following steps are required in the migration process.  · Use queries for extraction to mine data from SQL Server. Select specific statements to sort, filter, and limit the data in this step. Data extraction for large databases is done with the Microsoft SQL Server Management Studio tool.  · The extracted data cannot be directly migrated to Snowflake. It has to be processed and formatted so that the mined data type matches that permitted in Snowflake architecture. For JSON and XML data, a schema is not required before migration.  · Even after the data is processed and formatted, it still cannot be migrated directly into Snowflake. The processed data has to be first loaded into a staging area. There are two categories here – internal stage and external stage. An internal staging area can be customized with SQL statements and provides flexibility to users to allot file formats and other options to the named stages. External stages are locations that have specific interfaces where data can be loaded. At present, Snowflake supports Amazon S3 and Microsoft Azure as external stages. 

  5. · After these three steps, the data is ready to be migrated from SQL Server to Snowflake from the staged location. The Data Loading Overview tool of Snowflake is used for loading large and bulk databases. In such instances the PUT command is used to stage files, the COPY INTO command to transfer formatted data to an intended file, and the COPY command to migrate data from a staging area to Snowflake. It is different for small databases where the data loading wizard of Snowflake can be used for migration.    While loading a database from SQL Server to Snowflake,it has to be ensured that the system after migration only loads incremental data and complete refreshes are not required every time.  

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