API Connectors: What They Are and Why They’re Crucial to Legacy Integration

API connectors perform a crucial role in modern data integration processes. As the modern business environment relies on the generation and transfer of enormous amounts of data, these handy tools have become ubiquitous.

That’s because the problem of data silos is still a very real one, particularly for businesses that use legacy systems. Tackling this issue is a top priority for any organization looking to become more efficient in its operations, and API connectors can help.

But what actually are they? This article sets out to demystify API connectors and explain how they work. It also looks at why they’re so useful for integrating data between legacy systems and cloud-based applications.

A quick recap; what are APIs?

So, what is an API? First of all, the letters API stand for application programming interface. APIs are tools that hugely simplify the process of getting different types of software to communicate with each other.

APIs do this by establishing the rules and definitions that allow information to pass smoothly between systems. This is important because systems store and process data in a variety of ways. Without some way of translating between them, the data can’t be transferred.

Essentially, you can think of an API as acting like a data port on a computer. Except in this case, it’s connecting two software systems together rather than, say, a laptop and a video camera.

API vs. integration: What’s the difference?

Because they’re so useful, APIs are an extremely commonplace solution for integrating systems. However, the terms “API” and “integration” aren’t interchangeable, as they represent two different concepts.

The term “API” refers to the interface itself. In other words, an API is the lines of code that do the work of translating data between systems.

Integration, on the other hand, is the big-picture process that focuses on getting various software systems to work together to achieve a specified objective. For example, you might decide to integrate your CRM with a third-party application. An API could be one of the tools you’d use to do it.

There’s more than one way to implement data integration, though. Rather than APIs, you can sometimes choose native integrations. Native integration uses code written into the software itself that lets it communicate with other applications.

The choice between native integration vs. API approaches comes down to your business objectives and which pieces of software you want to get working together.

Plenty of modern software already offers native integration with popular tools at no extra cost, so there’s no need for additional application connectors. For instance, many business software suites offer native integration with the biggest social media platforms to help clients manage their social strategy effectively.

However, if you want an integration encompassing a more niche tool, you may have to find an alternative solution. In that case, using an API connector platform is often the simplest option.

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So, what is an API connector and what does it do?

Now, we come to the crucial question, “What is an API connection?”. Well, consider the laptop/video camera analogy mentioned earlier. In that situation, you can’t simply push the camera into the data port. You need to run the right kind of cable from the camera to the laptop to link the two devices.

API connectors perform a similar function in the world of data integration. An API connector translates the data on both sides into a common language so that data transfer can be implemented automatically between systems.

This is crucial because data structures and formats can differ significantly. API connectors often incorporate mapping and transformation features to convert data between formats.

They can also manage the flow of data between multiple systems, performing tasks in a specific order based on predefined workflows. This is particularly useful when it comes to more complex integrations where data has to be processed by different applications before arriving at its final destination.

A good application connector also comes equipped with mechanisms to deal with errors. Typical examples include retry policies for handling temporary failures or logging features to record the history of data exchanges for debugging purposes.

Then there’s the issue of performance optimization. This is an important aspect of API connectors, meaning it tends to be a key focus in development regardless of the data connector types being built. That’s simply because if performance is patchy, it can slow down data transfer, so the connection becomes unusable.

To prevent this, API connectors implement caching, request throttling, and other techniques to optimize the performance of data exchanges. This is particularly critical when dealing with APIs that have rate limits or if the job involves processing especially large volumes of data.

One big strength of OpenLegacy API connectors is that they allow you to access legacy systems in a variety of ways. For instance:

• Mainframes: API connectors act as a bridge between legacy mainframe sources and modern applications. That enables the extraction of data from sources such as VSAM files, all without relying on complex middleware.
• Midrange systems: You can integrate older IBMi systems with newer applications, so there’s no need to rely on outdated programming languages like COBOL and RPG.
• Databases: API connectors can create direct connections to legacy databases and convert the data held there into a usable format. Once again, bypassing traditional middleware.
• Packaged applications: With API connectors, you can solve the problem of dealing with complex customizations that have accumulated over time in packaged applications on legacy systems. Integration with modern systems is, therefore, simplified which enhances business agility and efficiency.
• Many other legacy assets and protocols: The customizability of API connectors means they’re very flexible and completely adaptable. They can deal with any kind of legacy system and speed up the development of new innovations.

Note that connectors built for APIs and the cloud are increasingly common, since the range of cloud-based business solutions available continues to expand rapidly. 

However, theoretically, you can use API connectors to align any digital systems. Which is why they’re so useful when it comes to working with data held on legacy systems.

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Why does your choice of API connector matter for legacy integration?

Selecting the right integration connectors is particularly important for legacy integration. That’s because the process can be significantly more challenging than data integration between two modern software platforms.

If you want to modernize legacy systems to align them with the cloud environment, the connectors themselves need to be designed to work in a technology that uses APIs.

This means they should be able to support distributed systems, microservices, and different deployment protocols (e.g., serverless environments). Not all API connectors can handle this, which is why choosing the right API connectors is vital, and why using a specialized API connector tool is becoming an ever more popular option.

A comparison with translating between human languages is an appropriate one. The closer the two languages are, the more straightforward the process tends to be. 

Suppose you’re translating a Dutch novel into German. In that case, any cultural references in the original text will probably already be well understood by the target readers, so they can just be left as they are.

But let’s say you’re translating a book from Japanese into English. There will be significant cultural context and linguistic complexities. That may mean you require some creative imagination to get the meaning across in a way that’s faithful to the nuances of the original text.

The equivalent in terms of data integration is that API connectors also need to deal with the context the data sits within. Integrating data between modern systems that are designed with today’s digital environment in mind can be a relatively straightforward process.

But if you want to integrate data from a legacy system like a mainframe into a 21st-century cloud-based tool, that’s more like translating Japanese into English.

For instance, you can’t simply translate COBOL COPYBOOKS to JSON one-to-one and leave it at that. You also have to find a way to manage the complex aspects of the mainframe itself. This could include issues such as:

• Accounting for different data types
• Handling different principles of operations
• Batch windows that might limit the availability of data
• Having a lack of testing environments

Some API connectors are specifically designed to cope with all of these challenges. Even so, choosing the right one can sometimes seem like an intimidating task. This is where OpenLegacy comes in.

OpenLegacy removes the burden of API connector choice

Using the OpenLegacy Hub hybrid integration platform takes all the uncertainty out of the connector API decision. All OpenLegacy connectors are designed specifically for the cloud and deployment via APIs. This means you don’t need to worry about whether you’re selecting the right connectors.

The OpenLegacy Hub also features a visual development environment that makes it straightforward to operate. You can select the legacy system from the comprehensive library of connectors. Then, you simply drag and drop to map the data, business logic, and outputs.

The overall effect is that this creates a reusable modern representation of the legacy asset in whatever format you prefer. When you want to create custom hybrid APIs, it’s easy to do this by selecting from the wide range of pre-built solution templates and then customizing them to suit your pipeline.

In other words, OpenLegacy Hub delivers a flexible, fast, and simple approach to leveraging data from your legacy systems without any need to worry about which API connectors to use.