Do you want to transfer your data from REST API to Microsoft SQL Server? Are you finding setting up the SQL Server REST API Integration challenging?

If yes, then you’ve landed at the right place! This article will answer all your queries & relieve you of the stress of finding a truly efficient solution.

Follow our easy step-by-step guide to efficiently transfer your data to Microsoft SQL Server from REST APIs.

Upon a complete walkthrough of this blog, you can successfully set up SQL Server REST API Integration and seamlessly transfer your data for a fruitful analysis.

It will further help you build a customized ETL pipeline for your organization.

Why is a Microsoft SQL Server REST API Useful?

Microsoft SQL Server supports many languages and various client libraries. But nowadays, enterprises are shifting towards more flexible and easy-to-create API-driven solutions that allow them to access the server or data using a single REST API interface.

Apart from programming a connection bridge between the Database and the endpoints, it also involves performance, security, and compliance.

Methods to Set Up SQL Server REST API Integration

There are multiple ways in which you can set up the SQL Server REST API Integration:

Method 1: Using Hevo Data to Set Up SQL Server REST API Integration

Hevo Data Logo.
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Hevo Data, a No-code Data Pipeline, helps you transfer data from REST APIs to Microsoft SQL Server & lets you visualize it in a BI tool.

Hevo is fully managed and completely automates not only loading data from 150+ Sources but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.

Its fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss.

It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.

It allows you to focus on key business needs and perform insightful analysis using various BI tools such as Power BI, Tableau, etc. 

Hevo Data focuses on two simple steps to help you connect REST API to SQL database:

  • Configure Source: Connect Hevo Data with your REST API source by providing a unique name for your pipeline and information about the method you want to use, choosing between GET and POST. You will also need to provide the URL for your API endpoint, data root for your API, and your credentials such as username and password to allow Hevo to access your data, along with information about your query params and API headers.
  • Integrate Data: Load data from REST APIs to Microsoft SQL Server by providing a unique name for your destination and your database credentials, such as username and password. To help Hevo connect with your Microsoft SQL Server database, you will also have to provide information such as the host IP, port number, and the name & schema of your database.

With this, you have successfully set up SQL Server REST API Integration.

All of the capabilities, None of the firefighting

Using manual scripts and custom code to move data into the warehouse is cumbersome. Frequent breakages, pipeline errors, and lack of data flow monitoring make scaling such a system a nightmare. Hevo’s reliable data pipeline platform enables you to set up zero-code and zero-maintenance data pipelines that just work.

Reliability at Scale – With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency. 

Monitoring and Observability – Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs. 

Stay in Total Control – When automation isn’t enough, Hevo offers flexibility – data ingestion modes, ingestion, and load frequency, JSON parsing, destination workbench, custom schema management, and much more – for you to have total control.    

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 you don’t face the pain of schema errors.

24×7 Customer Support – With Hevo, you get more than just a platform; you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform.

Moreover, you get 24×7 support even during the 14-day full-featured free trial.

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. 

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Method 2: Using Microsoft SQL Server Integration Services (SSIS) to Set Up SQL Server REST API Integration

The Microsoft SQL Server Integration Services(SSIS) is a robust component and functionality of the Microsoft SQL Server Database that allows users to carry out numerous complex data migration tasks easily.

It houses support for and provides various tools such as data warehousing tools that help automate ETL to some extent, workflow tools to automate the data migration process, and a diverse set of data integration tools that allow users to unify data.

It also supports connecting with REST API-based sources and lets users ingest data into their Microsoft SQL Server databases.

You can set up the SQL Server REST API Integration by leveraging the connection manager using the following steps:

Step 1: Defining a Data Flow Task

Defining a Data Flow Task: SQL Server REST API Integration.
Image Source: Self

To start setting up the SQL Server REST API Integration, you first need to define a new data flow-based task. You must specify the Microsoft SQL Server ADO.Net destination and new REST source.

To do this, go to the connection manager, add a new connection, and choose the connection type REST by selecting the REST option from the dropdown list.

This is how you can define a data flow task.

Step 2: Configuring Connection Properties

With your task now added, you need to configure the properties for the connection. To do this, you will have to specify the connection properties such as the REST URI, your credentials, and the authentication format, choosing between OAuth, HTTP, NTLM, and Digest, along with information about the incoming file format like JSON, XML, etc.

Configuring Data Mapping and Destination Properties: sql server rest api
Image Source: Self

Once you’ve provided the necessary information, you need to specify the “DataModel” property that helps map incoming data into database tables.

You can choose between the following options for the DataModel property:

  • Relational: This helps ensure that mapping for incoming data takes place in a way that maintains referential integrity.
  • Document: This helps map data into nested or hierarchical data documents.
  • Flattened Documents: This helps aggregate data from nested documents and their parent documents into a single table.

This is how you can configure the connection properties.

Step 3: Configuring Extraction Properties of REST Data Source

Configuring the Extraction Properties for REST Sources: sql server rest api
Image Source: Self

With your connection properties now configured, you must configure the REST source extraction properties.

To do this, you will need to have the “Create Global Objects” permission and provide the query that will help extract data from your data source.

Once you’ve done that, close the REST source and connect it to the ADO.NET-based destination.

Step 4: Configuring the Microsoft SQL Server Database

With all the necessary configurations now done, you now need to configure your Microsoft SQL Server destination database.

You can do this by providing the database name, tables, and information about the desired data access mode and choosing between views/tables.

Now, map the incoming data with the destination column and then click on the advanced option and specify the following properties:

  • BulkInsertFireTriggers: Should bulk insert fire triggers on destination tables.
  • BulkInsertOrder: Sort columns specified in ascending/descending order.
  • MaxInsertCommitSize: Maximum number of rows to insert in a single batch) 
  • DefaultCodePage: Code page to use if the source does not provide one.

You can now execute this workflow to start loading data from REST API to Microsoft SQL Server databases.

This is how you can set up the SQL Server REST API integration using the Microsoft SQL Server Integration Service (SSIS).

Limitations of Using Microsoft SQL Server Integration Services (SSIS)

Some of the limitations of using Microsoft SQL Server Integration Services (SSIS) for SQL Server REST API Integration include:

  • The Microsoft SQL Server Integration Service (SSIS) provides support only for the Microsoft SQL Server database. Hence, if your business data needs require using a diverse set of databases, then using SSIS will not work.
  • If your systems require you to delegate data storage or processing to a particular tool based on the data type, such as MongoDB or Neo4J for graph databases, then SSIS can limit your options.

Method 3: Using Custom Code Snippets to Set Up SQL Server REST API Integration

To start loading data from REST APIs, you must first leverage the JDBC driver’s “DriverManager” class to obtain and establish a connection with your Microsoft SQL Server instance.

You can use the following syntax for creating your connection URL:


Once you’ve set up the necessary configurations and created your connection URL, you need to create a statement object that will carry out SQL operations such as insert, delete, update, etc., and fetch results.

With your statement object ready, you will have to execute the insert command in a repetitive loop based on conditional logic.

Once you’ve executed the insert statement or any other operation, you must close the statement and connection object.

For example, if you want to insert, set, and update values in your Microsoft SQL Server database using APIs, you can do so using the following lines of code:

While (someCondition) {
// Specify the connection URL as per SQL server connection string.
        String connectionUrl = "jdbc:sqlserver://<YourServer>:<port>;databaseName=HevoMSSqlTest;user=<user>;password=<password>";

        try {
//LOAD the API driver 	
//Get a new Connection to SQL Server 
	Connection conn = DriverManager.getConnection(connectionUrl); 

// Create a statement object, this is the vehicle for carrying your SQL inserts				PreparedStatement stmt = conn.prepareStatement("INSERT into my_records" +" VALUES(?,?,?,?,?)");

// SET the values in your table columns 							
	stmt.setInt(1, 0);			
	stmt.setString(2, myString);					
	stmt.setString(4, myName);					
	stmt.setString(5, myRole);

//EXECUTE the update 					
	}// End of TRY block 
        catch (Exception e) {
        System.err.println("Error: ");

	finally {
// CLOSE the Statement and Connection objects 
} // END of While loop 

This is how you can develop custom code snippets that leverage the JDBC driver for Microsoft SQL Server to set up the SQL Server REST API Integration.

Limitations of Using Custom Code Snippets

Though you can efficiently set up SQL Server REST API Integration manually, several limitations are associated with this method. Some of the limitations include:

  • Using drivers requires keeping track of updates and manually updating them when new releases are available or when your technology stack(Java, Node.js, C++, Python) undergoes updates. Similarly, existing API calls and methods may depreciate with new versions and require upgrades.
  • To ensure smooth data transfers and high efficiencies, you will have to add/remove/change the new properties associated with your connections when any change occurs.
  • Working with APIs to load data requires strong technical knowledge to handle operations such as connection pooling, query optimization, compression, validation, etc.
Scale your Data Integration effortlessly with Hevo’s Fault-Tolerant No Code Data Pipeline

As the ability of businesses to collect data explodes, data teams have a crucial role in fueling data-driven decisions. Yet, they struggle to consolidate the data scattered across sources into their warehouse to build a single source of truth.

Broken pipelines, data quality issues, bugs and errors, and lack of control and visibility over the data flow make data integration a nightmare.

1000+ data teams rely on Hevo’s Data Pipeline Platform to integrate data from over 150+ sources in a matter of minutes. Billions of data events from sources as varied as SaaS apps, Databases, File Storage, and Streaming sources can be replicated in near real-time with Hevo’s fault-tolerant architecture.

What’s more – Hevo puts complete control in the hands of data teams with intuitive dashboards for pipeline monitoring, auto-schema management, and custom ingestion/loading schedules. 

This, combined with transparent pricing and 24×7 support, makes us the most loved data pipeline software on review sites.

Take our 14-day free trial to experience a better way to manage data pipelines.

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This article explains how to quickly load data from REST API to Microsoft SQL Server by setting up the SQL Server REST API Integration.

It provides in-depth knowledge about the concepts behind every step to help you understand and implement them efficiently.

These methods, however, can be challenging, especially for a beginner & this is where Hevo Data saves the day. 

Get started for Free with Hevo!

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Sign Up for a 14-day free trial and experience the feature-rich Hevo suite firsthand.

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Tell us about your experience setting up the SQL Server REST API integration! Share your thoughts in the comments section below!

Pratik Dwivedi
Freelance Technical Content Writer, Hevo Data

Pratik writes about various topics related to data industry who loves creating engaging content on topics like data analytics, machine learning, AI, big data, and business intelligence.

No-code Data Pipeline For SQL Server