The added complexity involved in orchestrating an ETL pipeline is one of the most challenging aspects of Salesforce to SQL Server Integration. You need to sort this issue to integrate your SQL Server with Salesforce to access and manipulate your Salesforce data in SQL Server for more advanced reporting.
Currently, both Salesforce and SQL Server do not provide a direct way of exporting objects from Salesforce into SQL Server. This post will introduce you to the different ways to carry out the integration based on your use case. You will learn how to connect Salesforce to SQL Server and replicate data seamlessly.
In this next section, you will learn how to replicate data from Salesforce to SQL Server using the Export and Import Wizards technique.
Exporting Data from Salesforce to SQL Server
Below are the two possible methods to export data from Salesforce to SQL Server:
Method 1: Connecting Salesforce to SQL Server Using Hevo
Using Hevo would be a much superior alternative to this method since it’s able to automate this ETL process, allowing your developers to focus on BI and not coding complex ETL pipelines.
Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. With integration with 150+ Data Sources (40+ free sources), we help you not only export data from sources & load data to the destinations but also transform & enrich your data, & make it analysis-ready.
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You can move data effortlessly with Hevo from Salesforce to SQL Server using the following steps:
Step 1: Authenticate and connect to your Salesforce account on the Hevo platform.
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Step 2: Connect your SQL Server to Hevo and transfer data instantly and set up Salesforce to SQL Server Integration.
Image Source: Self
By following the above steps, you easily export Salesforce data to SQL Server.
For detailed information check out:
Other Highlights of Hevo:
- Wide Range of Connectors: Instantly connect and read data from 150+ sources including SaaS apps and databases, and precisely control pipeline schedules down to the minute.
- In-built Transformations: Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface, or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
- Auto-Schema Management: Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps source schema with destination warehouse so that you don’t face the pain of schema errors.
- Transparent Pricing: Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow.
- Security: Discover peace with end-to-end encryption and compliance with all major security certifications including HIPAA, GDPR, SOC-2.
Ebury, a global Fintech company has to say this about using Hevo for their data integration needs:
With Hevo, our data is more reliable as it was compared to Fivetran at a way better pricing. Hevo allows us to build complex pipelines with ease and after factoring in the excellent customer service and reverse ETL functionality, it is undoubtedly the best solution available in the market.
– Juan Ramos, Analytics Engineer, Ebury
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Method 2: Export Data from Salesforce to SQL Server using Export and Import Wizards
In this section of the blog post, you will learn how to ETL data from Salesforce to SQL Server using the Salesforce Data Loader export wizard and the SQL Server import wizard. This method consists of the following:
Step 1: Export object records into CSV files using the Data Loader export wizard
- Log in to your salesforce application.
- Go to setup.
- Under Administer select Data Management > Data loader.
- Choose the appropriate version for your computer and download the file.
- Download Data Loader for Windows.
- Download Data Loader for Mac.
- Double click the saved file to install it on your PC.
- Go through the installation prompts until the installation is complete.
- Launch the Salesforce Data Loader export wizard by double-clicking on the desktop icon.
- Click Export.
- Enter your Salesforce username and password, and click Log in.
- Once you’re logged in, click Next.
- Select the object you wish to export. For example, you can select the Leads object. To view an expanded view of all the objects available for export, select Show all objects.
- Create the CSV file to export the data to and click Next.
- Create a SOQL (Salesforce Object Query Language) query for the data export. For example, for Lead data, you can select First Name, Last Name, Address, Email, Mobile, City, Lead Source, Lead Status, Campaign, Company, and Title in the query fields, and click Finish. As you follow the next steps, the CSV viewer displays all the lead names and the corresponding fields.
Step 2: Import the CSV files in your SQL environment using the SQL Server import wizard.
- Log into your SQL database using the SQL Server Management Studio.
- Create a table in your database where you will be importing the CSV file containing all your data.
- Right-click on your database and select Tasks > Import Data.
- Click the Next > button.
- For the Data Source, select Flat File Source.
- Use the Browse button to select the CSV file. Here you can configure how you want the data to be imported. Once you’re done, click on the Next > button.
- For the Destination, select the correct database provider. For example, for SQL Server 2016, you can use SQL Server Native Client 11.0. Enter the Server name. Check the Use SQL Server Authentication radio button. Enter the User name, Password, and Database before clicking on the Next > button.
- On the Select Source Tables and Views window, you can Edit Mappings before clicking on the Next > button.
- Check the Run immediately checkbox and click the Next > button.
- Click on the Finish button to run the package.
There you have it. You now have a solid foundation on how to export data from Salesforce to SQL Server.
Limitations of Manually Exporting Data from Salesforce to SQL Server
There is one caveat to this method and that is that this method does not support bulk import and therefore if you have multiple CSV files, you will have to load them one at a time. It also does not support automatic incremental updates since it’s a manual process.
Do you want a hassle-free method of transferring your data without the drawbacks of manually writing code? Enter Hevo. Sign up for a free trial today to simplify your data transfer process.
Reasons to Export Data from Salesforce to SQL Server
Salesforce offers a wealth of features that no other CRM program can match, including contact management, workflow development, task management, opportunity tracking, collaboration tools, customer engagement tools, analytics, and an easy-to-use dashboard that works on mobile devices. SQL Server offers improved performance thanks to its integrated transparent data compression and encryption features. Access controls and effective permission management tools are provided by SQL Server to help users protect sensitive business data.
When integrated together, moving data from Salesforce to SQL Server could solve some of the biggest data problems for businesses.
Method 3: Manualy Replicating Data from Salesforce to SQL Server
Step 1: Pull Data from Salesforce
a. Use the Salesforce REST API to pull data.
You can use CURL or Postman tools, or HTTP clients for your preferred language or framework, to interact with the REST API. Some recommendations:
- Apache HttpClient for Java
- Spray-client for Scala
- Hyper for Rust
- Ruby rest-client
- Python http-client
The Salesforce REST API supports oAuth 2.0 authentication. In order to load the data on a data warehouse, you must engage with the API’s resources and begin retrieving its data after completing the authentication process successfully.
Getting a list of all the resources we may access is simple. For instance, we can use curl to do the following operations:
curl https://na1.salesforce.com/services/data/v26.0/ -H "Authorization: Bearer token"
A typical response from the server will be a list of available resources in JSON or XML, depending on what you have asked as part of your request.
{
“sobjects” : “/services/data/v26.0/sobjects”,
“licensing” : “/services/data/v26.0/licensing”,
“connect” : “/services/data/v26.0/connect”,
“search” : “/services/data/v26.0/search”,
“query” : “/services/data/v26.0/query”,
“tooling” : “/services/data/v26.0/tooling”,
“chatter” : “/services/data/v26.0/chatter”,
“recent” : “/services/data/v26.0/recent”
}
Salesforce REST API is very expressive; it also supports a language called Salesforce Object Query Language (SOQL) for executing arbitrarily complex queries. For example, the following curl command will return the name fields of accounts:
curl https://na1.salesforce.com/services/data/v20.0/query/?q=SELECT+name+from+Account -H "Authorization: Bearer token"
and the result will look like the following:
{
"done" : true,
"totalSize" : 14,
"records" :
[
{
"attributes" :
{
Following the preparation of your customer and your successful connection to Salesforce, you must do the following actions:
- choose which API resources to pull out.
- Connect these resources to each data warehouse repository’s schema that you intend to utilize.
- convert information into it and
- Using the guidelines below, load the converted data into the repository.
b. Pull Data using Salesforce Streaming API
Using the Streaming API to communicate with SalesForce is an additional intriguing method. You create queries using it, and you receive notifications each time there is a change to any data that is registered to this query. For instance, the API will notify your preferred service by push notification whenever a new account is created. This is a very strong method that can ensure updates on a Data Warehouse repository in nearly real time.
However, to put anything like that into practice, you have to ensure that whatever data management infrastructure you develop meets your use case’s delivery semantic requirements while also taking into account the limits of both ends.
Step 2: Salesforce Data Preparation for Microsoft SQL Server
The proper mapping of any data to the appropriate data types is crucial when working with data sourced from online services, where the data is often serialized as JSON. It’s crucial to give appropriate thought to data type assignments since altering the data type might cause your database to go offline.
The most common method for importing SalesForce data into a SQL Server database is to construct a schema in which every API endpoint is mapped to a table. Every key in the SalesForce API endpoint response has to be mapped to a column in that table, and you need to make sure the conversion to a data format that is compatible with SQL Server is done correctly.
Step 3: Load data from Salesforce to MS SQL Server
The SQL Server Import and Export Wizard is one tool you may use to import data into your database. It will enable mass loading of data from several data sources that are supported by a graphical user interface.
Additional SQL Server databases, Oracle databases, Flat Files, Access Data Sources, PostgreSQL, MySQL, and Azure Blob Storage can all be imported. You should absolutely think about leveraging the Azure Blob Storage connection, especially if you are using a managed version of MS SQL Server on Azure. With the Import and Export Wizard, you may load data as Blobs on Azure and your MS SQL Server database will sync with it.
The bcp tool is an additional method for importing large amounts of data into a SQL Server database, both on Azure and on-premises. This command-line utility was created especially for using an MS SQL database to load and unload data in bulk.
Lastly, you can utilize BULK INSERT SQL commands for compatibility purposes, particularly if you are managing databases from various manufacturers.
Conclusion
This article talks about the 2 simple methods you can use to transfer data from Salesforce to SQL Server. You can either connect them manually or a third-party tool like Hevo.
Hevo, a No-code Data Pipeline, helps you transfer data from 150+ data sources (Including 50+ Free Sources like Salesforce) in a fully automated and secure manner without having to write the code repeatedly.
Visit our Website to Explore Hevo
Hevo, with its strong integration with 150+ sources & BI tools, allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiff.
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How do you move your data from Salesforce to SQL Server? Let us know in the comments below.
With over a decade of experience, Suraj has played a crucial role in architecting and developing core frontend modules for Hevo. His expertise lies in building scalable UI solutions, collaborating across teams, and contributing to the open-source community, showcasing a deep commitment to innovation in the tech industry.