Why Should You Migrate Database SQL Server to Databricks

Databricks is a software company founded by the creators of Apache Spark. Its USP is that it can combine data lakes and data warehouses into a Lakehouse architecture. The process involves manually building a data pipeline with a Python script typically through three easy steps.  

·      *  Setting up SQL Server as a source connector

·      *  Setting up Databricks Lakehouse as a destination connector

·      * Deciding which data to move from SQL Server to Databricks and the periodicity

Before you can transfer data from SQL Server to Databricks, some basic functions have to be carried out.

·     *   Have a SQL Server account from where to transfer the data

·    *    Have a Databricks Lakehouse account as the target

·      *  An active cloud account


Moving Data From SQL Server To Databricks

Moving data from SQLServer to Databricks is a simple three-stage process. The data is first extracted from the SQL Server using the source connector. This data is then processed and formatted to match a structure that is supported by Databricks using the schema provided. Finally, the processed data is loaded into Databricks using the destination connector.

The purpose of this data migration is to allow enterprises to leverage their SQL Server data to gain added and advanced analytics and insights within the Databricks Lakehouse. 

Benefits of Migrating SQL Server to Databricks

There are several benefits of this type of migration.

·      *  Enhanced data processing speeds

·    *    Easy scalability of resources to meet immediate demands.

·      *  A collaborative environment that facilitates cross-functional team cooperation, production, and innovation.

Databricks provides enhanced security features and governance tools that make data compliant with regulatory standards after migrating from SQL Server to Databricks.

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