REST API is one of the most common approaches to easily interact with sites on the web and extract the required data for business. After you have integrated with REST API, you can simply consolidate the data in Cloud-based Data Warehousing solutions like Microsoft Azure. Azure provides a wide variety of cloud computing services with On-demand scalability of both storage and compute resources. And in this blog post, we’re going to learn about connecting REST API to Azure.
You can easily get data from REST API in Azure Data Factory via the REST connector provided by the Azure Data Factory. With API Authentication & your SQL Database credentials, you can quickly get started with REST API Azure Integration.
Now, without any further ado, let’s dive into Azure Data Factory REST examples of connection!
What is Azure?
Microsoft Azure is a public Cloud Computing platform that allows you to access and manage Microsoft’s cloud services and resources. The cloud service includes best-in-class computation, Data Analytics, Storage, networking, IoT, migration, artificial intelligence, and other machine learning, integration, management tools, developer tools, security, databases, DevOps, media identity, and web services. For instance, Microsoft Azure SQL Database is a completely managed PaaS(Platform as a Service) offering continuous upgrading, patching, backups, and monitoring of the database.
Key Features of Azure
- Improved Backup & Data Recovery: Azure allows you to back your data from any language or operating system & also lets you decide the frequency of the data backup cycle. As a preventive measure, Azure stores 3 copies of your in 3 different places as well as three separate copies in a remote Azure data center.
- Manageability: Features such as Automatic Patch Management for virtual machines allow you to focus on your core objectives. Azure scales automatically as your business scales, thereby providing a seamless experience.
- Analytics Capabilities: Cortana Analytics, Stream Analytics, Machine Learning, and SQL services are some of the brilliant analytics tools provided by Azure to assist you in discovering new business opportunities, improving customer service, and making informed decisions.
- Flexibility: Microsft Azure allows you to work with multiple programming languages, including Java, Node Js, and C#. After developing your applications, Azure also provides a platform to test and deploy them.
Hevo, a fully managed Data Pipeline platform, can help you automate, simplify, and enrich your data replication process in a few clicks. Hevo provides a Native REST API connector to load data from non-native or custom sources to any destination, including Azure.
Here are reasons to try Hevo:
- Data Transformation: Hevo provides a simple interface to perfect, modify, and enrich the data you want to transfer.
- Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
- Scalable Infrastructure: As your sources and data volume grow, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Faster Insight Generation: Hevo offers near real-time data replication, so you can generate real-time insights and make faster decisions.
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What is a Rest API?
An Application Programming Interface(API) is a set of rules that describe how devices or applications connect and interact with each other. The API establishes an accurate method for you to write a program that requests services from an operating system or other application. A REST API is an API that follows the design protocols of REST (Representational State Transfer Architectural Style). This is generally employed for Web APIs that use HTTP requests to access and use data. However, there are critical differences between API and REST API, which is explained in this blog in detail.
Key Features of REST API
REST API offers the following eye-catching features:
- Simpler: Compared to SOAP, REST API is a much faster alternative that is simpler to implement. Relying on the HTTP standard, REST API allows you to use different data formats such as XML, JSON, HTML, etc. Since it is a lightweight solution, it is widely used for mobile app projects, internet of things devices, etc.
- Stateless: When using REST APIs, no client content is stored on the server between requests. All the Information about the session’s state remains with the client instead.
- Scalable: Since the Client & Server are separated, it can be quickly scaled. It allows developers to easily integrate with REST APIs.
- Error Messages: Owing to the REST Architecture, error messages can be added to assist developers.
Here’s another blog that discusses a few best REST API best practices for 2023. Take a gander for to make an informed decision.
Why Connect REST API to Azure?
REST API allows you access to a pool of data on the web. You can leverage the power of data available from these sources by extracting it using a REST connector. Azure Data Factory provides a simple UI to implement Azure Data Factory REST API migration. With the On-demand scalability of both compute & storage resources, you can effectively use Azure products like SQL Database to quickly analyze your data and gain meaningful business insights.
How to Connect REST API to Azure?
You can set up the Azure SQL REST API Migration using Azure Data Factory. Using the Copy Data Tool, you can easily create a pipeline to move data from your REST source to various Azure sources like Azure SQL API Database or Azure Blob Storage. In this article, REST is selected as the data source and Azure SQL Database as the destination. Before you begin using the REST API to Azure connector, you need to have an Azure Data Factory. If not done already, you can set up your Data Factory using the Official Azure Documentation.
To get started with the REST API to Azure Integration process, you can follow the simple steps given below:
- Step1: In your Azure Data Factory Workspace, browse to Pipelines Tab and navigate to Pipeline > New Pipeline.
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- Step 2: Type “Copy Data” in the search Activities box and drag n drop the Copy Data option in the whitespace on the right. In the Source tab, click on the + New button to add your data source.
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- Step 3: Type “REST” in the search box and click on the REST icon. Click on the Continue button to choose REST as your source.
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- Step 4: Click on the Linked Service drop-down menu and select the + New option.
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- Step 5: Now, you can enter the REST API URL from where you want to extract the data and the type of Authentication it requires such as Anonymous, Basic, AadServicePrincipal, OAuth2ClientCredential, and ManagedServiceIdentity. For this article, the freely available public API https://dummy.restapiexample.com/api/v1/employees is selected for the sample dataset. Since it is publicly available, the authentication type is Anonymous. Click on the Test Connection button to verify the data transfer connection for REST API to Azure & then click on the Create button.
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- Step 6: Now, according to your use case you can configure the Source Request settings. For this REST API to Azure connector example, the default configuration is selected. You can also click on the Preview Data option to verify if the correct data is being read.
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- Step 7: Next, click on the Sink tab to select your destination. Click on the + New button and type “SQL Database” in the search box. Select the Azure SQL Database icon and click on the Continue button.
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- Step 8: Click on the Linked Service drop-down menu and select the + New option. Now, to use the REST API to Azure connector, you need to enter your Azure SQL Database credentials and provide the basic details. Once done, click on the Test connection button and then click on the Create button.
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- Step 9: In the Set Properties window, select your table & schema and click on the OK button once done.
- Step 10: Now, in this step for connecting REST API to Azure, you can configure the Sink settings. In the Table option field, click on the Auto-Create Table option to let Azure directly make a table in the SQL Database. Click on the Open option next to the Sink Dataset field, and provide the schema & the table name.
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- Step 11: Go to the Mapping Tab and click on the Import Schema button. The desired column names will be shown on your screen. You can now delete the columns that you don’t need to transfer from REST API to Azure and then select the desired data type for these columns from the drop-down menu. Click on the Collection Reference checkbox and finally click on the Debug button to start the REST API to Azure Migration process.
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- Step 12: To verify the data transfer from REST API to Azure, you can open up your SQL Azure Database and check the Table by executing a SELECT query. This completes the process to connect REST API to Azure.
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Conclusion
In this article, you learned how to effectively replicate data from REST API to Azure in 12 easy steps. Azure Data Factory allows you to add your required REST API URL and the authentication method to connect REST API to Azure products such as Azure SQL Database & Blob Storage. You can easily enter your credentials for the SQL Database and choose the columns you want to replicate from the REST API data source.
As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for complete performance analysis of your business. However, it is a time-consuming and resource-intensive task to continuously monitor the Data Connectors. To achieve this efficiently, you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse, BI Tool, or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.
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Hevo, a No-code Data Pipeline can Ingest Data in Real-Time from a vast sea of 150+ sources like REST API to a Data Warehouse or a Destination of your choice. It is a reliable, completely automated, and secure service that doesn’t require you to write any code!
If you are using REST API as your data source and searching for a seamless alternative to Manual Data Integration, then Hevo can effortlessly automate this for you. Hevo’s strong integration with 150+ Connectors (Including 40+ Free Sources), allows you to export, load, transform & enrich your data to make it analysis-ready.
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Share your experience of connecting REST API to Azure! Let us know in the comments section below!
Sanchit Agarwal is an Engineer turned Data Analyst with a passion for data, software architecture and AI. He leverages his diverse technical background and 2+ years of experience to write content. He has penned over 200 articles on data integration and infrastructures, driven by a desire to empower data practitioners with practical solutions for their everyday challenges.
