Integrating APIs with SQL Server streamlines data flow and enhances the functionality and versatility of SQL Server, providing a dynamic platform for real-time data updates and interactions.
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.
Follow our step-by-step guide to efficiently transfer your data from REST APIs to Microsoft SQL Server.
It will further help you build a customized ETL pipeline for your organization.
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 Automated Data Pipeline Platform to Set Up SQL Server REST API Integration
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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 Data 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, the 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 parameters 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.
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Method 2: Using Microsoft SQL Server Integration Services (SSIS) to Set Up SQL Server REST API Integration
The Microsoft SQL SSIS (Server Integration Services) 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 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
Image Source: Self
To start setting up the SQL Server REST API Integration, you must first 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.
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 Data Model 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
Image Source: Self
With your connection properties now configured, you must configure the REST source extraction properties.
To do this, you must 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 load 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) only supports 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 storage 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:
protocol//[hosts][/database][?properties]
Once you’ve set up the necessary configurations and created your connection URL, you must 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 must 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
Class.forName("com.microsoft.jdbc.sqlserver.SQLServerDriver");
//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(3,myAddress);
stmt.setString(4, myName);
stmt.setString(5, myRole);
//EXECUTE the update
stmt.executeUpdate();
}// End of TRY block
catch (Exception e) {
System.err.println("Error: ");
e.printStackTrace(System.err);
}
finally {
// CLOSE the Statement and Connection objects
stmt.close();
conn.close();
}
} // 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 must 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.
Why integrate REST API to SQL Server?
1. Real-Time Data Updates
REST APIs have the capability to get data in real-time which help you to store fresh data whenever it comes.
2. Seamless Data Integration
The API calls allow you to easily retrieve data from external sources through API calls and map it to the right SQL Server tables. This builds a unified and consolidated data repository.
3. Automation and Efficiency
You can carry out scheduled tasks or triggers to fetch and import data at regular intervals automatically or in response to specific events. This avoids the requirement for manual intervention for data entry.
4. Data Transformation and Enrichment
You can perform any data modification and enrichments before storing it in SQL Server. It also allows manipulation of the retrieved data, logic, cleaning and normalising the data, and adding it with additional data, increasing the quality and use of the data.
5. Data Validation and Error Handling
The validation and error handling mechanisms allow only valid and consistent data to be stored in the database. This avoids the risk of data corruption or any inconsistencies in data.
6. Centralized Data Storage and Management
The REST APIs help to centralize the data, removing data silos. This helps to store, query, and analyze data faster and effectively. This also makes data governance, security, and other compliance efforts smooth.
7. Improved Data Analysis and Reporting:
SQL Server has tools and functions for querying, aggregating, and visualizing data. This helps you to draw data-driven conclusions.
8. Scalability and Performance:
You can leverage SQL Server’s indexing, partitioning, and query optimization abilities for fast and reliable processing of data, even when there is a high volume of data.
Conclusion
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.
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Additional Read for Refreshing Basics
What is SQL Server?
SQL Server is Microsoft’s relational database that has the ability to store, manage, and analyze your data centrally. It stores data in tables which are interconnected by unique vital constraints. The latest versions of SQL Server have many capabilities including data encryption, schema reading, and data analysis. These capabilities also include integrations with business intelligence tools that help you build reports and optimize your ETL workflows.
What is REST API?
REST API is an API that adheres to some rules for your application and services to a properly communicate with each other. It is also called RESTful API as it is constrained to REST architecture. They are very helpful in accessing web services in a flexible way without huge processing abilities.
Gain a deeper insight into SQL Server Integrations with these essential reads:
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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 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.