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Replicate data SQL Server to Snowflake

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Replicate data SQL Server to Snowflake

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  1. Replicating Data From Microsoft SQL Server to Snowflake Microsoft SQL Server is a database management system where various applications can be run on a single machine either across the web or on a local area network. It supports Microsoft’s .NET framework out of the box and blends into the total Microsoft ecosystem. Why then would organizations want to replicate SQL Server data to Snowflake? 

  2. Snowflake is a cloud-based data warehousing solution that resolves many issues inherent in traditional solutions. Further, the process to replicate data SQL Server to Snowflake is easy and can be completed in a few clicks.

  3. Here are a few benefits for migrating data to Snowflake – •Enhanced performance – There are separate compute and storage facilities in the cloud and users pay only for resources used.  •Replicating different data structures – Snowflake supports JASON, Avro, XML, and Parquet data. Both structured and unstructured data can be stored natively in Snowflake. 

  4. •Access to varying workloads – Quick access is enabled to the same data by multiple workgroups working on multiple workloads. Snowflake ensures that even in these cases there is no downgrading of performance.  •Supports several cloud vendors – The architecture of Snowflake supports a wide range of cloud vendors. Hence businesses can use the same tools to analyze data of various cloud vendors. Snowflake is continually updated and new cloud vendors are routinely added to the architecture. 

  5. These are some of the advantages open to organizations to replicate data SQL Server to Snowflake. • Now, what is the process and steps to be taken for migrating data to Snowflake? •Extract data from SQL Server – The most common method is to use queries for extraction and Select statements are used to sort, filter, and limit the data to be retrieved. Where bulk data and databases have to be exported in text, CSV, or SQL queries format, Microsoft SQL Server Management Studio tool has to be used.  •Processing data before export – Before loading data to Snowflake, the same has to be processed so that the data structure matches the data types supported by Snowflake. It is not necessary though to define a specific schema beforehand when loading JSON or XML data into Snowflake.  

  6. •Temporary staging data files – Data files have to be uploaded temporarily into an Internal Stage or External Stage before inserting MySQL data into a Snowflake table. An Internal Stage is created exclusively with relevant SQL Statements and makes loading data effortless by assigning a file format. External stages supported by Snowflake are currently Amazon S3 and Microsoft Azure.   •Loading data to Snowflake – The Data Loading Overview module of Snowflake helps users to replicate data SQL Server to Snowflake. It is done through PUT command to stage files and COPY INTO table command for loading processed data into an intended table in Snowflake.   With the right skill sets, data administrators can easily implement the process. 

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