Azure Synapse Pathway — Accelerate your Datawarehouse Migration to Azure Synapse
In my previous article, we talked about the things that you need to consider before migrating an on-premises data warehouse to Azure Synapse.
In this article, we will talk about one of the key phases of the data warehouse migration project life cycle, i.e Translating the existing code that is written in the current system (on-premises SQL server) to the new system (Azure Synapse).
To convert the existing SQL code, customers have to either manually rewrite all the SQL code in the current system or invest large amounts of their budget for an outside practice to rewrite or convert their code (Ref:Microsoft)
As you all know, in the migration project life cycle, Translate Code is the key phase where customers have to invest most of their time and money, but fortunately, Microsoft introduced a new tool called Azure Synapse Pathway to accelerate the Migration process
Azure Synapse Pathway helps customers accelerate their migration process by translating the existing SQL code (Data Definition Language (DDL) and Data Manipulation Language (DML) scripts) to Azure Synapse. This significantly reduces the migration time and cost
So let's see how we can use this tool in the migration process
- Click here to download and install the Azure Synapse Pathway
Below is the list of databases that are currently available in the Azure Synapse Pathway ( the list may grow big in the future)
For this example, we are going to use SQL Server.
Choose the input directory for your scripts to Translate, I generated all the DDL and DML scripts from my on-premises SQL server and saved them to the folder as shown below
Now select the output directory for the translated scripts → click on Translate
The tool translates the scripts and saves the translated code to the output directory along with the results.csv as shown below.
The results.csv provides a list of syntax errors and recommendations as shown below, we can use this list to create migration tasks to the respective development teams in the Azure DevOps.
Keep in mind that, this is still in a public preview state and also we cannot expect a 100% successful code translation from the tool. but it definitely saves the manual effort needed to translate the SQL code.
Hope you enjoyed reading this article, see you in my next article until then stay safe and help out others in any way you can.
