Salesforce to Azure SQL Data Warehouse

This page provides you with instructions on how to extract data from Salesforce and load it into Azure SQL Data Warehouse. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Salesforce?

Salesforce, a cloud-based software-as-a-service platform, is the most popular CRM application in use today. Salesforce is amazingly customizable, has tons of integration functionality, and includes almost too many bells and whistles to count. Companies can use it to do everything from managing account planning to time management and team collaboration.

What is Azure SQL Data Warehouse?

Azure SQL Data Warehouse is a cloud-based petabyte-scale columnar database service with controls to manage compute and storage resources independently. It offers encryption of data at rest and dynamic data masking to mask sensitive data on the fly, and it integrates with Azure Active Directory. It can replicate to read-only databases in different geographic regions for load balancing and fault tolerance.

Getting data out of Salesforce

Step one is to get all of that data out of Salesforce. Salesforce provides many APIs for its products that can deliver data on accounts, leads, tasks, and more. You can find a list of APIs on one of the company's helpdesk posts with some direction on when and how to use each API. By looking through that post, you can get an idea of which API makes the most sense for your use case.

For our purposes, we'll use the REST API with SOQL (Salesforce Object Query Language), but the same data is available using other protocols, including streaming for real-time receipt of data.

Sample Salesforce data

The Salesforce Rest API can return JSON- or XML-formatted data depending on your preference. Here's what a sample response might look like in JSON format:

{
    "done" : true,
    "totalSize" : 14,
    "records" : 
    [ 
        {  
            "attributes" : 
            {    
                "type" : "Account",    
                "url" : "/services/data/v20.0/sobjects/Account/001D000000IRFmaIAH"  
            },  
            "Name" : "Test 1"
        }, 
        {  
            "attributes" : 
            {    
                "type" : "Account",    
                "url" : "/services/data/v20.0/sobjects/Account/001D000000IomazIAB"  
            },  
            "Name" : "Test 2"
        }, 

        ...

    ]
}

Loading data into Azure SQL Data Warehouse

SQL Data Warehouse provides a multi-step process for loading data. After extracting the data from its source, you can move it to Azure Blob storage or Azure Data Lake Store. You can then use one of three utilities to load the data:

  • AZCopy uses the public internet.
  • Azure ExpressRoute routes the data through a dedicated private connection to Azure, bypassing the public internet by using a VPN or point-to-point Ethernet network.
  • The Azure Data Factory (ADF) cloud service has a gateway that you can install on your local server, then use to create a pipeline to move data to Azure Storage.

From Azure Storage you can load the data into SQL Data Warehouse staging tables by using Microsoft's PolyBase technology. You can run any transformations you need while the data is in staging, then insert it into production tables. Microsoft offers documentation for the whole process.

Keeping Salesforce data up to date

At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.

Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Salesforce.

And remember, as with any code, once you write it, you have to maintain it. If Salesforce modifies its API, or the API sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.

Easier and faster alternatives

If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.

Thankfully, products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Salesforce data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Azure SQL Data Warehouse data warehouse.