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How Matillion Built A Framework For Extracting Data From Any API

How Matillion Built A Framework For Extracting Data From Any API Image

Matillion is a cloud-native data integration and transformation platform for modern data architectures. It allows users to extract, load, and transform data from various sources into cloud data warehouses and lakes. Matillion provides a visual interface for building data pipelines and supports integration with popular cloud platforms such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). It enables organizations to accelerate data integration and analytics processes, enabling faster and more efficient decision-making.

In this blog post, we will go over how to construct a framework for obtaining data from an API. We will begin by defining the problem, and requirements and building a framework. 

The Problem

  • Data extraction from numerous APIs
  • Getting the data into your cloud.
  • There are different data sources, and each one's API can be complicated. 
  • We need a framework that makes it possible to extract data from any of these sources. 
  • A framework should be adaptable, simple to change, and user-friendly.

The Requirements

  • Matillion requires a framework that enables data extraction from any of these data sources.
  • This framework must be flexible, easily editable, and allow for use by the customer.

The Framework

  • The data connection is the essential component that uses the framework to obtain your data. Several APIs might be used by the connector.
  • The environments (sandbox, production) and versions (v1, v2) of an API might vary, and each version has its own endpoints (/invoices, /accounts) that users can use to retrieve data. 
  • These interactions provided us with the primary basis on which we could construct our framework.
  • Once the fundamental structure was established, we considered the items we would need to perform an API request and page the data, such as a URI, authentication, paging instructions, etc. 
  • All of them seemed to fit together like puzzle pieces that could be defined at any level of the framework.


  • A string of characters called a "URI," which stands for "Uniform Resource Identifier," is used to differentiate one resource from another.


  • This makes sure that only users with valid credentials can access secure systems.

Paging Standards

A system will save and retrieve content from a device's secondary storage to the primary repository as part of the memory management process known as paging.

For instance, assume any business with the name "com name" has a production environment for its Ads API with two separate versions and two separate endpoints.

A certain kind of authentication is necessary for one of the endpoints. Here is how our framework would accommodate that:

  • The only other place an Auth Type is defined is for the Ad Accounts endpoint in the V2 API, which we have done here at the environment level. 
  • All of the endpoints in the actual production environment will therefore utilize Auth Type 1, with the exception of the Ad Accounts endpoint for V2, which uses a different type of authentication. 
  • With this flexibility, we can handle unusual situations like endpoints with unique authentication requirements.
  • Using that, we've created a framework that we can use to make API calls programmatically.
  • Thus, it enables the creation of a customized connection, enabling Matillion to be connected to almost any data source.
  • Matillion is clearly focused on semi- or non-structured data sources based on the list of over 70 possible connections.


The user doesn't need to have substantial coding experience to get started and set up a straightforward ETL pipeline because the UI is totally straightforward. Users can build their own connectors to collect data from your restful API source systems, organize that data, and have it available for downstream analytics in only a few minutes.

By leveraging this framework, organizations can overcome the complexities associated with the various APIs and unlock valuable insights.  Matillion's commitment to reliability, flexibility, and ease of use ensures that data professionals can streamline their workflows and focus on deriving actionable intelligence from the extracted data.

Transform Your Data Pipeline With Matillion

If you are looking to enhance your data integration capabilities and streamline API data extraction, the Matillion framework is a powerful tool worth exploring. Take the next step towards data-driven decision-making by implementing Matillion's framework. 

Don't miss out on the benefits that the Matillion framework brings to your data integration process. Act now and revolutionize the way you extract data from APIs.


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